Miracle-dz/UniFAR-FTUs huggingface dataset:
Appropriability Mechanisms and the Performance of digital startups: The Moderating Role of Technology Innovativeness

It has become an important issue for digital startups to figure out how to realize value creation and value capture in open innovation. Using data from the CPSED II database, we examined the impact of digital startups' appropriability mechanisms on firm performance, as well as the moderating role of technology innovativeness. According to empirical results, both intellectual property rights and downstream capabilities of digital startups have a positive impact on firm performance, but technology innovativeness reduces the positive impact of downstream capabilities on firm performance. The study's findings are useful for advising digital startups on how to gain a competitive advantage through open innovation.
Upscaling Fog Computing in Oceans for Underwater Pervasive Data Science Using Low-Cost Micro-Clouds

Underwater environments are emerging as a new frontier for data science thanks to an increase in deployments of underwater sensor technology. Challenges in operating computing underwater combined with a lack of high-speed communication technology covering most aquatic areas means that there is a significant delay between the collection and analysis of data. This in turn limits the scale and complexity of the applications that can operate based on these data. In this article, we develop underwater fog computing support using low-cost micro-clouds and demonstrate how they can be used to deliver cost-effective support for data-heavy underwater applications. We develop a proof-of-concept micro-cloud prototype and use it to perform extensive benchmarks that evaluate the suitability of underwater micro-clouds for diverse underwater data science scenarios. We conduct rigorous tests in both controlled and field deployments, using river and sea waters. We also address technical challenges in enabling underwater fogs, evaluating the performance of different communication interfaces and demonstrating how accelerometers can be used to detect the likelihood of communication failures and determine which communication interface to use. Our work offers a cost-effective way to increase the scale and complexity of underwater data science applications, and demonstrates how off-the-shelf devices can be adopted for this purpose.
The Influence of Disease Avoidance Motive on the Economic Behavior Ethics under the Impact of Pandemic: A Moderated Mediation Model

Objective: As one of the basic social motives, Disease Avoidance Motive is the deep psychological factor behind many social behaviors. Since the emergence of the COVID-19 and its continuous spread across the world at the end of 2019, the ever-changing and recurring COVID-19 pandemic has increased people's fear and rejection of the threat of infectious diseases, and activated people's Disease Avoidance Motive, which has remained at a high level for a long time. This study takes Disease Avoidance Motive as the starting point, introduces COVID Control Regulations as the intermediary, and disease vulnerability as the regulator, to explore the influence of Disease Avoidance Motive on Economic Behavior Ethics. Methods: Regression analysis, SPSS Statistics and Moderated Mediation Model were applied and 524 random respondents were surveyed through Basic Social Motivation Scale, Pandemic Norm Compliance Questionnaire, Economic Behavior Ethics Questionnaire and Scale of Perceived Vulnerability to Disease. Results: (1) Disease Avoidance Motive positively predicts Economic Behavior Ethics; (2) COVID Control Regulations play a mediating role between Disease Avoidance Motive and Economic Behavior Ethics (3) Perceived Vulnerability to Disease positively moderates the direct effect of Disease Avoidance Motive on Economic Behavior Ethics. Conclusion: Under the moderation of Perceived Vulnerability to Disease, Disease Avoidance Motive exerts an influence on the Economic Behavior Ethics through COVID Control Regulations.
Effects of tensile and compressive strain on the luminescence properties of AlInGaN/InGaN quantum well structures

We report on the luminescence properties of AlInGaN/In0.08Ga0. 92N quantum wells (QWs) subjected to a variable amount of lattice mismatch induced strain, including wells with zero strain, compressive strain, and tensile strain. The primary peak emission energy of a 3 nm In0.08Ga0. 92N QW was redshifted by 236 meV as the stress in the well was changed from −0.86% (compressive) to 0.25% (tensile). It was also found that the photoluminescence intensity of quantum wells decreased with increasing strain. A lattice matched 9 nm QW exhibited a luminescence intensity that is three times greater than its highly strained counterpart. The potential applications of this strain engineering will be discussed.
Adaptation Strategies to Increase Business Competitiveness in the Digital Era: an Empirical Study of Local Freight Firms in Thailand

Digitization plays a significant role in shaping modern business operations. The notion of digitalization is also included in Thailand’s recent national economic development policy, known as Thailand 4.0. Under the policy, rooted in the industry 4.0 concept, the country promotes economic growth with innovation and creativity and tries to move towards the digital economy. This paper presents an empirical study examining the business adaptation of local family firms facing opportunities and business challenges caused by the Thailand 4.0 policy and the digitalization motivation. It delivers empirical evidence on entrepreneurship development in local Thai cross-border freight family businesses trying to change to innovative firms. The researchers employed a qualitative research approach to investigate five purposively selected firms from Nakhon Phanom province of the North-East region of Thailand. The research data was collected using documentary analysis and semi-structured interviews with the owner-managers of the selected firms. Study results are delivered under two themes: developing innovative family entrepreneurship and digitalization in local cross-border freight firms. The results show that digitalization is adopted to improve three primary areas for strategic improvement in the transportation industry, including inventory, transport, and location strategies. Family power and control are founded to positively support the family business transformation towards industry 4.0 via business digitalization. Trained employees to gain sufficient knowledge related to digital transformation is also essential. The paper also identifies areas requiring further improvements, including systematic support from public authorities and reliable technology to help widen and sustain domestic and international business partnership networks.
A Live Environment to Improve the Refactoring Experience

Refactoring helps improve the design of software systems, making them more understandable, readable, maintainable, cleaner, and self-explanatory. Many refactoring tools allow developers to select and execute the best refactorings for their code. However, most of them lack quick and continuous feedback, support, and guidance, leading to a poor refactoring experience. To fill this gap, we are researching ways to increase liveness in refactoring. Live Refactoring consists of continuously knowing, in real-time, what and why to refactor. To explore the concept of Live Refactoring and its main components — recommendation, visualization, and application, we prototyped a Live Refactoring Environment focused on the Extract Method refactoring. With it, developers can receive recommendations about the best refactoring options and have support to apply them automatically. This work helped us reinforce the hypothesis that early and continuous refactoring feedback helps to shorten the time needed to create high-quality systems.
Improving Face Anti-spoofing via Advanced Multi-perspective Feature Learning

Face anti-spoofing (FAS) plays a vital role in securing face recognition systems. Previous approaches usually learn spoofing features from a single perspective, in which only universal cues shared by all attack types are explored. However, such single-perspective-based approaches ignore the differences among various attacks and commonness between certain attacks and bona fides, thus tending to neglect some non-universal cues that contain strong discernibility against certain types. As a result, when dealing with multiple types of attacks, the above approaches may suffer from the uncomprehensive representation of bona fides and spoof faces. In this work, we propose a novel Advanced Multi-Perspective Feature Learning network (AMPFL), in which multiple perspectives are adopted to learn discriminative features, to improve the performance of FAS. Specifically, the proposed network first learns universal cues and several perspective-specific cues from multiple perspectives, then aggregates the above features and further enhances them to perform face anti-spoofing. In this way, AMPFL obtains features that are difficult to be captured by single-perspective-based methods and provides more comprehensive information on bona fides and spoof faces, thus achieving better performance for FAS. Experimental results show that our AMPFL achieves promising results in public databases, and it effectively solves the issues of single-perspective-based approaches.
Design and Implementation of Wireless IoT Device for Women’s Safety

Abstract—Nowadays, women face imminent risk of sexual harassment, rape and molestation in the streets as male predators roam around in search of their potential targets. In this precarious scenario, women needs to be protected in the street for their safety. To address these challenges, in this paper, we propose a wearable device that will protect and enhance the safety of women. This goal is achieved by analyzing the user’s pulse rate and oxygen measurements and updating them on the Blynk IoT web server. The user’s pulse-rate and blood oxygen saturation is determined by acquiring raw heart-rate and oxygen values from a pulse oximeter and oxygen sensor installed at the heart of the device. Real-time monitoring of user data is achieved by transferring sensor data to the Blynk IoT web server. This wireless device is specifically programmed to continuously monitor the user’s pulse-rate and oxygen values and react in case of a danger situation. It does so by detecting the abnormal pulse-rate and oxygen values, after which it sends the alert text message along with the location and live video streaming to the guardian’s mobile device via the Tasker app. Meanwhile, the alarm starts ringing. Besides, we validate our system architecture using different real time test cases. Moreover, we present a comparison of our proposed architecture with existing literature’s.
Europa Clipper Preliminary Design Review Propellant Slosh Analysis

Propellant slosh was analyzed for both the oxidizer and the fuel for the Europa Clipper propulsion system. Slosh was examined for various fill fractions for cases where acceleration was on the order of magnitude of 10 -2 m/s 2 using the computational fluid dynamics software package STAR-CCM+ and at various fill fractions for cases where acceleration was on the order of magnitude of 10 -5 m/s 2 using Surface Evolver. Equivalent mechanical model parameters were derived from the CFD data using MATLAB for both the higher and the lower acceleration slosh cases. These parameters were plotted and can be used to interpolate mechanical model parameters at fill fractions not analyzed by CFD or Surface Evolver.
Sex-dependent noradrenergic modulation of premotor cortex during decision-making

Rodent premotor cortex (M2) integrates information from sensory and cognitive networks for action selection and planning during goal-directed decision making. M2 function is regulated by cortical inputs and ascending neuromodulators, including norepinephrine (NE) released from the locus coeruleus (LC). LC-NE has been shown to modulate the signal to noise ratio of neural representations in target regions prior to decision execution, to increase the salience of relevant stimuli. Using rats performing a two-alternative forced choice task after administration of a β adrenergic antagonist (propranolol), we show that action planning in M2 is mediated by β adrenergic signaling. Loss of β adrenergic signaling results in failure to suppress irrelevant action plans in M2 that disrupts decoding of cue related information, delays decision times, and increases trial omissions, particularly in females. Furthermore, we identify a potential mechanism for the sex bias in behavioral and neural changes after propranolol administration via differential expression of β2 receptors across sexes, particularly on local inhibitory neurons. Overall, we show a critical role for β adrenergic signaling in M2 during decision making by suppressing irrelevant information to enable efficient action planning and decision execution.
Systematic evaluation of anatomical details on transcranial electric stimulation and transcranial magnetic stimulation induced electric fields in a non-human primate model

Non-human primates (NHPs) have become key for translational research in noninvasive brain stimulation (NIBS). However, in order to create comparable stimulation conditions to humans it is vital to evaluate and match electric fields across species. Numerical models to simulate electric fields are an important tool for experimental planning in NHPs and translation to human studies. It is thus essential to evaluate how anatomical details in NHP models affect NIBS electric fields. Here, we create a highly accurate head model of a non-human primate (NHP) from 10.5 T MR data. We systematically evaluate how muscle tissue and head size (due to different MRI fields of view) affect simulation results in transcranial electric and magnetic stimulation (TES and TMS). Our findings indicate that the inclusion of muscle can affect TES electric field strength up to 29.5% while TMS is largely unaffected. Additionally, comparing a full head model to a cropped head model illustrates the impact of head size on electric fields for both TES and TMS. We find opposing effects between TES and TMS with an increase up to 13.5% for TES and a decrease up to 21.5% for TMS for the cropped head model compared to the full head model. Our results provide important insights into the level of anatomical detail needed for NHP head models and can inform future translational efforts for NIBS studies. Highlights We created a high resolution non-human primate FEM head model from 10.5 T MR data. We ran transcranial electric and magnetic stimulation (TES and TMS) simulations to evaluate the effects of muscle and head size on the induced electric field in the brain. We simulated both isotropic and anisotropic muscle conductivities. Muscle tissue can greatly affect simulation results for TES (increase electric field strength by up to 29.5%), but not for TMS. There are opposing, but large effects of using a full head model versus a cropped head model for both TES (increase up to 13.5%) and TMS (decrease of up to 21.5%)
Substrate profiling of the metalloproteinase ovastacin – Implications for its physiological function in mammalian fertilization

The metalloproteinase ovastacin is released by the mammalian egg upon fertilization and cleaves a distinct peptide bond in zona pellucida protein 2, a component of the enveloping extracellular matrix. This limited proteolysis causes zona pellucida hardening, abolishes sperm binding and thereby regulates fertility. Accordingly, this process is tightly controlled by the plasma protein fetuin-B, an endogenous competitive inhibitor. At present, little is known about how the cleavage characteristics of ovastacin differ from closely related proteases. Physiological implications of ovastacin beyond ZP2 cleavage are still obscure. In this study, we employed N-terminal amine isotopic labeling of substrates (N-TAILS) contained in the secretome of mouse embryonic fibroblasts to elucidate the substrate specificity and the precise cleavage site specificity. Furthermore, we were able to unravel the physicochemical properties governing enzyme-substrate interactions. Eventually, we identified several potential physiological substrates with significance for mammalian fertilization. These data suggest that ovastacin might regulate sperm-oocyte interaction and fertility beyond zona pellucida hardening. Graphical Abstract
A Diamond Shaped Compact Dual-band Metamaterial Absorber for 𝑲 𝒖 and 𝑲 𝒂 Band Applications

: Metamaterial-based polarization insensitive absorbers have completely overcome the conventional absorbers, just because of their notable artificially engineered properties that lead towards the device compactness and thickness reduction. Here, we proposed a compact diamond shape polarization-insensitive absorber with the addition of “+” symbol slits for 𝐾 𝑢 and 𝐾 𝑎 band, 5G, satellite, 5G communication, and antennas isolation applications. The complete structure of the metamaterial absorber is 3.8 ×3.8 × 1.6 mm3, which is backed with a perfect electric conductor layer of 0.03 mm. The maximum absorption of 97 and 99.987% were observed at 24.3 and 29.5 GHz in 𝐾 𝑢 and 𝐾 𝑎 , respectively. The metamaterial absorber (MA) maintained its maximum absorption under the angular stability analysis by varying the polarization angle with a normal incident angle. However, under the TE and TM modes analysis, a minimum of 94% absorption was observed at 24.3 GHz. Thus, the results of MA proved that our suggested may be used for practical applications such as radar surface absorption, remote sensing, antennas isolation satellite, and 5G communication.
Web Semantics: Science, Services and Agents on the World Wide Web

While the availability of large-scale online recipe collections presents opportunities for health consumers to access a wide variety of recipes, it can be challenging for them to discover relevant recipes. Whereas most recommender systems are designed to offer selections consistent with users’ past behavior, it remains an open problem to offer selections that can help users’ transition from one type of behavior to another, intentionally. In this paper, we introduce health-guided recipe recommendation as a way to incrementally shift users towards healthier recipe options while respecting the preferences reflected in their past choices. Introducing a knowledge graph (KG) into recommender systems as side information has attracted great interest, but its use in recipe recommendation has not been studied. To fill this gap, we consider the task of recipe recommendation over knowledge graphs. In particular, we jointly learn recipe representations via graph neural networks over two graphs extracted from a large-scale Food KG, which capture different semantic relationships, namely, user preferences and recipe healthiness, respectively. To integrate the nutritional aspects into recipe representations and the recommendation task, instead of simple fusion, we utilize a knowledge transfer scheme to enable the transfer of useful semantic information across the preferences and healthiness aspects. Experimental results on two large real-world recipe datasets showcase our model’s ability to recommend tasty as well as healthy recipes to users.
Landscape or local? Distinct responses of flower visitor diversity and interaction networks to different land use scales in agricultural tropical highlands

Land use change has been identified as a cause for biodiversity loss and has significant effects on pollinators and their interactions with plants. Interaction network analyses complement diversity estimators by providing information on the stability and functionality of the plant-pollinator community in an ecosystem. However, how land use changes affect insect diversity, and the structure of their plant-insect interaction networks, could depend on the intensity of the disturbance but also may be a matter of scale. Our study was carried out in a tropical highland landscape dominated by intense, yet diverse, small-scale agriculture. We studied the effects of land use, at a landscape scale, and local cover and plant ecological descriptors, at a local scale; on diversity descriptors of insect pollinator communities, the abundance of the most frequent flower visitors, and their interaction networks. Seminatural vegetation favored insect flower visitors at both scales. At the landscape scale, human settlements positively influenced bee diversity, and seminatural areas favored the abundance of frequent hoverfly and bumblebee species. At the local scale, bare soil cover negatively influenced honeybee abundance while flower-rich covers positively related to bumblebee abundance. Only local scale variables had influence on network metrics. Bare soil cover was related to higher network specialization, probably due to a low rate of honeybee interactions. Flower-rich covers negatively influenced network connectance but favored modularity. These results suggest that flower resources, provided by weed areas and flowering crops, promote a high rate of interactions between trophic levels and a non-random structure in the interaction networks that may be helping to sustain network stability. Our results highlight the role of seminatural vegetation, at both scales, in maintaining stable insect pollinator communities and interactions in heterogeneous agricultural landscapes of the tropics.
Abnormal expression of cortical cell cycle regulators underlying anxiety and depressive-like behavior in mice exposed to chronic stress

Background The cell cycle is a critical mechanism for proper cellular growth, development and viability. The p16INK4a and p21Waf1/Cip1 are important regulators of the cell cycle progression in response to internal and external stimuli (e.g., stress). Accumulating evidence indicates that the prefrontal cortex (PFC) is particularly vulnerable to stress, where stress induces, among others, molecular and morphological alterations, reflecting behavioral changes. Here, we investigated if the p16INK4a and p21Waf1/Cip1 expression are associated with behavioral outcomes. Methods Prefrontal cortex mRNA and protein levels of p16INK4A and p21Waf1/Cip1 of mice (six independent groups of C57BL/6J, eight mice/group, 50% female) exposed from 0 to 35 days of chronic restraint stress (CRS) were quantified by qPCR and Western Blot, respectively. Correlation analyses were used to investigate the associations between cyclin-dependent kinase inhibitors (CKIs) expression and anxiety- and depression-like behaviors. Results Our results showed that the PFC activated the cell cycle regulation pathways mediated by both CKIs p16INK4A and p21Waf1/Cip1 in mice exposed to CRS, with overall decreased mRNA expression and increased protein expression. Moreover, correlation analysis revealed that mRNA and protein levels are statistically significant correlated with anxiety and depressive-like behavior showing a greater effect in males than females. Conclusion Our present study extends the existing literature providing evidence that PFC cells respond to chronic stress exposure by overexpressing CKIs. Furthermore, our findings indicated that abnormal expression of p16INK4A and p21Waf1/Cip1 may significantly contribute to non-adaptive behavioral responses.