Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Constituents, Intellectual Structure, and Collaboration Patterns in Journal of International Marketing: An Analytical Retrospective

This study presents a retrospective on Journal of International Marketing using bibliometrics. The study finds that the journal’s run has been characterized by continuous growth in publications and citations, with a dominant contribution base of authors from the United States. Authors have consistently shown a strong preference for quantitative research, with a decline in preference for qualitative research and a negligible increase in preference for mixed-methods research in recent years. The major themes in the journal include global branding, internationalization, cross-cultural marketing, and international relationship marketing. An exploration of the factors affecting article citations reveals that article attributes such as the conceptual method, empirical method, article length, title length, article age, and number of keywords play significant roles in increasing the number of citations. Authors affiliated with nonacademic institutions also have a significant and positive influence on total citations. The article concludes with directions for further research.
A System-Level Exploration of Binary Neural Network Accelerators with Monolithic 3D Based Compute-in-Memory SRAM

Binary neural networks (BNNs) are adequate for energy-constrained embedded systems thanks to binarized parameters. Several researchers have proposed the compute-in-memory (CiM) SRAMs for XNOR-and-accumulation computations (XACs) in BNNs by adding additional transistors to the conventional 6T SRAM, which reduce the latency and energy of the data movements. However, due to the additional transistors, the CiM SRAMs suffer from larger area and longer wires than the conventional 6T SRAMs. Meanwhile, monolithic 3D (M3D) integration enables fine-grained 3D integration, reducing the 2D wire length in small functional units. In this paper, we propose a BNN accelerator (BNN_Accel), composed of a 9T CiM SRAM (CiM_SRAM), input buffer, and global periphery logic, to execute the computations in the binarized convolution layers of BNNs. We also propose CiM_SRAM with the subarray-level M3D integration (as well as the transistor-level M3D integration), which reduces the wire latency and energy compared to the 2D planar CiM_SRAM. Across the binarized convolution layers, our simulation results show that BNN_Accel with the 4-layer CiM_SRAM reduces the average execution time and energy by 39.9% and 23.2%, respectively, compared to BNN_Accel with the 2D planar CiM_SRAM.
The tribological performance of a long chain alkyl phenylboric ammonium derivative and its interaction with ZDDP

A long chain alkyl phenylboric ammonium derivative (DBBM) was synthesized as a lubricating additive. The tribological performances of DBBM and combinations of DBBM and ZDDP as additives were evaluated, which suggests that DBBM has better tribological properties than ZDDP. X-ray absorption near edge structure spectroscopy was used for the analysis of thermal films and tribofilms. The results indicate that the boron in additive mainly forms trigonal and tetrahedral coordination boron both in thermal films and tribofilms, while sulfur mainly generates iron sulfate in thermal films and iron sulfide, iron disulfide, and iron sulfate in tribofilms. It also can be found that it is more likely to form low valence sulfur when the concentration of ZDDP increases in the combinations.
Adoption of high‐performance work systems in small and medium‐sized enterprises

This paper investigates the factors inﬂuencing the adoption of high-performance work systems (HPWS) in Chinese small and medium-sized enterprises (SMEs). The paper is based on a sample of 207 SMEs, which covers many of the ownership types and business sectors. The results of the correlation and regression analyses indicate that organizational factors have stronger explanatory power in predicting the adoption of HPWS than institutional factors. Speciﬁcally, top management support, perceived impact of HPWS, and organizational size are the three main predictors. The ﬁndings suggest that using management innovation theories to understand the underlying reasons associated with the adoption of HPWS is promising. The paper argues for the use of management innovation theories to explore the efﬁcacy of institutional factors more fully.
Lung Nodule Classification in CT Images Using 3D DenseNet

Lung cancer is the main malignant tumour affecting the health of residents in China. Automatically discriminating benign and malignant pulmonary nodules can facilitate the early detection of lung cancer, which reduces lung cancer mortality. The rising quantity of public available lung CT datasets made it possible to use deep learning approaches for lung nodules malignancy classification. Unlike most of the previous models that focused on 2D convolutional neural nets (CNN), here we explore the use of the DenseNet architecture with 3D filters and pooling kernels. The performance of the proposed nodule classification was evaluated on publicly available LUNA16 dataset, a subset of lung image database consortium and image database resource initiative dataset (LIDC/IDRI). It achieved a 92.4% classification accuracy. The proposed method provides an independent module with encouraging prediction accuracy that can be easily incorporated with a lung cancer computer-aided diagnosis system.
Dinámica espacio-temporal de la producción regional de diseños industriales en México

El objetivo de esta investigacion consiste en analizar la evolucion de la distribucion espacio-temporal de los disenos industriales en los estados de Mexico. La contribucion a la literatura empirica sobre innovacion estriba en estudiar, con una nueva base de datos, una forma de innovacion ampliamente ignorada en los estudios internacionales como son los disenos industriales, y por otro, su evolucion distributiva condicionada a la interaccion espacial. A partir del enfoque de cadenas de Markov espaciales propuesto por Rey (2001), los resultados sugieren la presencia de un proceso de divergencia en la produccion regional de disenos industriales caracterizado por una distribucion multimodal impulsado por las regiones vecinas ubicadas en las clases muy bajas, bajas o medios
A Review of Car-Following Models and Modeling Tools for Human and Autonomous-Ready Driving Behaviors in Micro-Simulation

The platform of a microscopic traffic simulation provides an opportunity to study the driving behavior of vehicles on a roadway system. Compared to traditional conventional cars with human drivers, the car-following behaviors of autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) would be quite different and hence require additional modeling efforts. This paper presents a thorough review of the literature on the car-following models used in prevalent micro-simulation tools for vehicles with both human and robot drivers. Specifically, the car-following logics such as the Wiedemann model and adaptive cruise control technology were reviewed based on the vehicle’s dynamic behavior and driving environments. In addition, some of the more recent “AV-ready (autonomous vehicles ready) tools” in micro-simulation platforms are also discussed in this paper.
Continuous in-home walking speed monitoring in older people with a low-cost ambient sensor: Results of a feasibility study

BACKGROUND: Walking speed predicts important clinical outcomes in older adults and is one of the most significant indicators of frailty. OBJECTIVE: To test whether it is feasible to measure walking speed frequently and unobtrusively in the home. METHODS: A longitudinal feasibility study was conducted comprising the installation and monitoring of continuous measurement walking speed sensors in twenty frail older adults’ homes for a period of twelve weeks (eighteen participants completed the study). Manual walking speed, frailty level and health status were measured at four-weekly intervals. Qualitative interviews were conducted at the end of the study to assess participants’ attitudes to the sensors and to the concept of continuous in-home walking speed measurement. RESULTS: There was a high degree of variance to the number of walking speed measurements recorded by each participant’s sensor (median 1942.39, range 2-3617). Participants indicated acceptability of both the sensor within the home and the concept of in-home walking speed measurement. CONCLUSIONS: Where regular measurement was achieved, the results indicate that walking speed might be better viewed as a distribution rather than a single figure, taking into account the natural variation to walking speed in daily life. This study demonstrates the feasibility of continuous ambient in-home walking speed monitoring of older adults with a low-cost, easily deployed device.
Gendered tourism experiences in China: exploring identity, mobility, and resistance online

ABSTRACT This paper presents research exploring the narratives Chinese women and men share online regarding gendered tourism experiences. Data were collected from 260 blog postings and resulting discussion threads on Chinese social media travel sites from March to November 2019. Search keywords included ‘gender,’ ‘women,’ ‘identity,’ ‘safety,’ ‘reasons women travel,’ ‘men’s resistance to women’s travel,’ and ‘sexual harassment. ’ Through a critical discourse analysis of travel blog postings, we found negative constructions of women who travel embedded in Confucian values of women as humble, invisible to the public eye, and immobile. Concurrently, bloggers expressed joy in discovering one’s self through travel, as well as anger at the ways in which Chinese women travellers are demonized online. Finally, we consider that while travel blog postings in some ways resist negative stereotypes of Chinese women travellers, ultimately Confucian ideals which discourage female expressions of anger and the valuing of women as family caregivers prevail.
Adoption of green innovations by SMEs: an investigation about the influence of stakeholders

PurposePursuing sustainable development has become a necessity for all types of businesses, owing to the increasing sensitivity of stakeholders towards pollution and environmental degradation related to economic activities. To sustain this approach, investments supporting green innovations (GIs) are required. The paper investigates how stakeholders affect the choices of companies to pursue sustainable development objectives through the use of GIs.Design/methodology/approachA sample of 222 innovative Italian SMEs was collected and analysed using the partial least squares structural equation modelling technique and the importance performance map analysis.FindingsThe authors found that the stakeholders with not-contractual ties with SMEs affect GIs. Among stakeholders with not-contractual ties only workforce represents a strong stimulus to eco-innovate. Anyway, contrary to expectations, public administrations exert a negative influence; that is, they appear to hinder SMEs approach towards GIs.Practical implicationsThis paper contributes to filling the knowledge gaps about the factors stimulating innovative SMEs' investments in GIs. Specifically, by analysing the stakeholders' influences, many policy indications emerge, such as extending facilities and regulations, encouraging partnerships and networking and attracting private and institutional investors.Originality/valueUntil now, the prominent interest of researchers and policymakers has been focused almost exclusively on large manufacturing corporations because of their higher ecological footprints and the belief that SMEs are supposed to be mainly followers rather than first adopters of innovations. But in many international areas, the role of SMEs is widely predominant, and these SMEs chiefly operate in the service sectors.
Software Defined Networking: A review on Architecture, Security and Applications

Throughout the development of the network, the Software Defined Networking(SDN) paradigm introduced the transition of conventional networks by decoupling the forwarding hardware from the network’s control logic. The SDN architecture enables networks to track traffic actively and detect threats to promote network forensics, alteration of security policy, and insertion of security services. We discuss SDN-related technologies in this paper. In particular, we are attempting to cover the key components of SDN: architecture, security, and its implementations hoping that our efforts will help researchers set relevant and practical directions for future SDN research. In a nutshell, this paper highlights the current and future directions for secured SDN. This paper examines the architecture of SDN where we discuss the network-building methods that arise in the case of the network control being removed from the continuity with the purpose of planning. We further explore the need of guarding access, veracity, and confidentiality of the resources and data, coupled with the myriad security options available for SDN. Lastly, we discuss the diversity bestowed by SDN in different sectors.
Complementary chain competition and fluorescence quenching detection of Deoxynivalenol and analytical applications using a novel aptamer

ABSTRACT Deoxynivalenol (DON) is a mycotoxin commonly found in cereals and animal feeds, which also is a carcinogen easily soluble in water. So it has drawn considerable interest in food safety. In this study, a specific aptamer named DON-A16 was developed from an immobilized ssDNA library by affinity chromatography column-based the SELEX. The complementary chain competition method for DON detection was established, and its limit of detection (LOD) was 488 ng/mL. Graphene oxide-based fluorescence quenching was developed using DON-A16 with fluorescein (FAM) label; its LOD was 200 ng/mL, and the detection time was 3 h. The recovery rate of fluorescence quenching was also detected in different samples (oat, wheat flour, corn), which showed the commercial DON ELISA kit led to an increase in repeatability, satisfactory recovery and consistency. The three-dimensional structure and the main binding site of of DON-A16 was ultimately obtained by molecular docking simulation.
Why Do Countries Request Assistance from International Monetary Fund? An Empirical Analysis

This paper investigates the determinants behind persistent and prolonged stays under the International Monetary Fund (IMF) program and its effectiveness, using panel data consisting of 70 countries that have requested IMF support multiple times, during the period 1980–2018. By employing panel survival analysis, we conclude that weak economic indicators, e.g., current account deficit, high debt service ratio, low GDP, are the main reasons that force a country to reach out to the IMF support program. We further extend our analysis to investigate the effectiveness of the IMF program by dividing our sample into two groups, based on income level. To overcome the issue of endogeneity, we implement the panel instrumental two-stage least squares (2SLS) fixed-effect model. In the light of our analysis, we find a contemporaneous positive impact of the IMF fund program on the economic growth of upper middle-income countries, while, for low-income countries, its contemporaneous impact is insignificant, but becomes visible over time.
Political Identity and Preference for Supplemental Educational Programs

The market for supplemental educational programs (SEPs)—tutorials, educational materials, summer programs—has burgeoned. Thus, it is important to understand factors that may influence parents’ choices for SEPs. This article examines how parents’ political identity affects their preference for SEPs contingent on their focus on self. Using two main educational orientations—conformance orientation and independence orientation—the authors argue that SEPs with conformance-oriented pedagogy may be preferred more by conservative parents due to their higher need for structure. This association of political identity with preference for SEPs is moderated by self-focus. Counterintuitively, when using political orientation to target messages for SEPs, firms should frame messages to focus parents on themselves for identity-consistent effects to manifest. Five studies, including a field study, test this theorizing and replicate key results using different measures of political identity and self-focus.
Gradient nanostructured titanium stimulates cell responses in vitro and enhances osseointegration in vivo

Background Though titanium (Ti) is widely used as dental materials in the clinic, effective methods to treat Ti for higher surface biological activity still lack. Through Surface mechanical attrition treatment (SMAT) technology we could endow Ti with gradient nanostructured surface (GNS Ti). To investigate the biocompatibility of GNS Ti for its further application in dental implant field, we study the effects of GNS Ti on cell responses in vitro and osseointegration of the implant with surrounding bone tissues in vivo. Methods In this study, GNS Ti was fabricated by SMAT. In vitro experiment, we co-cultured GNS Ti with bone mesenchymal stem cells (BMSCs), surface characterization was detected by transmission electron microscope (TEM). Adhesion, proliferation and differentiation of BMSCs were evaluated by scanning electron microscope (SEM), MTT, flow cytometry (FCM), alkaline phosphatase (ALP) and osteocalcin (OCN) tests. In vivo experiment, the GNS Ti was implanted into the rabbit mandible. Osteogenesis and osseointegration were evaluated by Micro CT, toluidine blue staining, and immunohistochemical staining at 4, 8, and 12 weeks postoperatively. Results Both results showed that compared with the coarse grained (CG) Ti, the GNS Ti stimulated the adhesion, proliferation, and differentiation of BMSCs and improved osteogenesis and osseointegration. Conclusions This study indicates that gradient nanostructured Ti is a promising material for dental implant application.
Frequency comb generation in whispering gallery mode silica microsphere resonators

Optical frequency combs (OFC) using different kinds of whispering-gallery-mode (WGM) microresonators have already shown different applications and especially their applications in fiber optical communication systems as replacements of laser-arrays. For this application the free spectral range (FSR) of 200 GHz or less is desirable. Besides the fabrication material for microspheres, the resonator radius can be modified to change the FSR. In this paper use of silica microspheres for OFC represents an inexpensive alternative over the other microcombs: microring, microdisk, and microtoroid. We experimentally present a microsphere fabrication process from a different kind of silica (SiO2) fibers by use of the hydrogen-oxygen melting technique. We experimentally review the OFC generation process the main microresonator parameters as FSR, Q-factor and evaluate the resulting WGM resonator generated OFC comb light source for further applications. An OFC was excited inside a 166 μm silica microsphere WGM resonators using a 1548 nm laser light. The obtained broadband OFC spanned from 1400-1700 nm with FSR of (397 ± 10) GHz.
Analysis of Stokes shift spectra for distinguishing human prostate cancerous and normal tissues using machine learning methods

Early detection of prostate cancer is critical for the success of cancer therapy. It is believed that the biochemical changes that cause the optical spectra changes would appear earlier than the histological aberration. The aim of this ex vivo study was to evaluate the ability of Stokes Shift Spectra (S3) to identify human prostate cancerous tissues from the normal. Fifteen (15) pairs of with pathologically confirmed human prostate cancerous and normal tissues underwent Stokes Shift Spectra measurements with selective wavelength interval of 40 nm. The spectra were then analyzed using machine learning (ML) algorithms to classify the two types of tissues. The ML algorithms including principal component analysis (PCA) and nonnegative matrix factorization (NMF) were used for dimension reduction and feature detection. The characteristic component spectra were used to identify the key fluorophores related to carcinogenesis. The results show that these key fluorophores within tissue, e.g., tryptophan, collagen, and NADH, have different relative concentrations between cancerous and normal tissues. A multi-class classification was performed using support vector machines (SVMs). A leave-one- out cross validation was used to evaluate the performance of the classification with the gold standard histopathological results as the ground truth. The results with high sensitivity and specificity indicate that the S3 method is effective for detecting changes of fluorophore composition in human prostate tissues due to the development of cancer.
Photocatalysis: a promising technology for wastewater treatment

Photocatalysis is a phenomenon, where an electron-hole pair is generated on exposing semiconducting materials to light of suitable energy. Thus, the chemical reactions that occur in the presence of a semiconductor and light are collectively termed as photocatalytic reactions. Photocatalytic reactions are mainly classified into two categories : (i) homogeneous photocatalysis, where substrate and photocatalyst both exist in the same phase and (ii) heterogeneous photocatalysis, in which substrate and photocatalyst exist in different phases. Different dyes and some soluble coordination compounds
Cluster Analysis of Short Sensory Profile Data Reveals Sensory-Based Subgroups in Autism Spectrum Disorder

Autism spectrum disorder is a common, heterogeneous neurodevelopmental disorder lacking targeted treatments. Additional features include restricted, repetitive patterns of behaviors and differences in sensory processing. We hypothesized that detailed sensory features including modality specific hyper- and hypo-sensitivity could be used to identify clinically recognizable subgroups with unique underlying gene variants. Participants included 378 individuals with a clinical diagnosis of autism spectrum disorder who contributed Short Sensory Profile data assessing the frequency of sensory behaviors and whole genome sequencing results to the Autism Speaks’ MSSNG database. Sensory phenotypes in this cohort were not randomly distributed with 10 patterns describing 43% (162/378) of participants. Cross comparison of two independent cluster analyses on sensory responses identified six distinct sensory-based subgroups. We then characterized subgroups by calculating the percent of patients in each subgroup who had variants with a Combined Annotation Dependent Depletion (CADD) score of 15 or greater in each of 24,896 genes. Each subgroup exhibited a unique pattern of genes with a high frequency of variants. These results support the use of sensory features to identify autism spectrum disorder subgroups with shared genetic variants.