Miracle-dz/UniFAR-FTUs huggingface dataset:
Achieving Green Innovation in Energy Industry through Social Networks, Green Dynamic Capabilities, and Green Organizational Culture

This research paper aims to evaluate the effect of social networks on the green innovation of energy sector firms working around the globe. The study also evaluated green dynamic capabilities’ mediating, and green organizational culture’s moderating role in the association of the social networks and green innovation. The study will help electricity production and distribution firms to become more environmentally proactive and achieve green innovation. For this research, study data were collected from employees working in the energy sector firms of Pakistan. Standardized scales were adapted from previous studies and a questionnaire was developed using ‘Google Docs’ and distributed using Facebook. From different energy sectors of Pakistan,476 respondents filled the questionnaires. To examine the research hypotheses, we chose energy firms that act as small and medium enterprises and face problems in the achievement of green innovation. For testing the proposed relationships, descriptive statistics, regression, and correlation analyses were used. The results supported all the hypotheses of the study. Current research has various theoretical and practical implications for managers of the energy industry, and governments.
Efficient interpolation of high‐frequency domain data by phase smoothing

In this paper, a novel phase‐smoothing method is proposed to efficiently interpolate the fine resolution frequency data from sparse samples in the high‐frequency range. This is achieved by taking the effect of the complex exponential term e−jkr in the electromagnetic field into account, which causes the oscillation in the system response especially in the high‐frequency domain. By phase‐smoothing, even though the magnitude of the field quantity is unchanged, both real and imaginary parts of the frequency response become smoother. The interpolation is performed separately for both real and imaginary parts so that the sample rate required for accurate reconstruction is significantly reduced. The interpolation is carried out by the matrix pencil method, the coefficients of which are calculated by using the total least squares implementation to improve accuracy. Several numerical examples are presented to illustrate the applicability of this unique phase‐smoothing method in ultra‐high‐frequency bands.
Hierarchical fusion robust Kalman filter for clustering sensor network time‐varying systems with uncertain noise variances

For the clustering time‐varying sensor network systems with uncertain noise variances, according to the minimax robust estimation principle, based on the worst‐case conservative system with conservative upper bounds of noise variances, applying the optimal Kalman filtering, the two‐level hierarchical fusion time‐varying robust Kalman filter is presented, where the first‐level fusers consist of the local decentralized robust fusers for the clusters, and the second‐level fuser is a global decentralized robust fuser for the cluster heads. It can reduce the communication load and save energy resources of sensors. Its robustness is proved by the proposed Lyapunov equation method. The concept of robust accuracy is presented, and the robust accuracy relations of the local, decentralized, and centralized fused robust Kalman filters are proved. Specially, the corresponding steady‐state robust local and fused Kalman filters are also presented, and the convergence in a realization between the time‐varying and steady‐state robust Kalman filters is proved by the dynamic error system analysis method. A simulation example shows correctness and effectiveness. Copyright © 2013 John Wiley & Sons, Ltd.
A Slotted Compact Four-port Truncated Ground Structured MIMO antenna for Sub-6 3.4 GHz 5G Application

|A novel high performance four-port multiple input multiple output antenna is suggested for 5G application functioning at 3.4 GHz band. The antenna design measures an inclusive volume of 32 mm (cid:2) 32 mm (cid:2) 0 : 8 mm 3 . The broad frequency bandwidth, excellent gain, decreased interelement gap, and eﬀective isolation within the MIMO components of the proposed system are clearly novel. Each antenna in the four-element MIMO system has been situated orthogonally to the others while maintaining a small size and good result. The antenna has exceptional average total eﬃciency in the 5G sub-6 GHz spectrum and is in good agreement with the measured results. It also oﬀers a high realized gain compared to prior MIMO antennas. The antenna has a high impedance matching whose isolation is about (cid:0) 28 dB, computed envelope correlation coeﬃcient smaller than 0.10, channel capacity loss average value less than 0.2 bits per second per hertz, and the diversity gain about 10 dB. The typical peak realized antenna gain of the oﬀered MIMO antenna is also delivered with a high radiation eﬃciency at the frequency of 3.4 GHz. The re(cid:13)ection coeﬃcient, mutual coupling, radiation pattern, current distribution, and gain of antennas are all measured and explained. The design has a compact high volume and adequate bandwidth with good accomplished gain making the antenna very strong for 5G application.
Cytotoxic Activity of Polyphenol Extracts from Three Oregano Species: Hedeoma patens, Lippia graveolens and Lippia palmeri, and Antiproliferative Potential of Lippia graveolens against Two Types of Breast Cancer Cell Lines (MDA-MB-231 and MCF-7)

Oregano infusions have traditionally been used to treat some diseases related to inflammation and cancer; also, some species have shown antiproliferative activity on cancer cell lines, for example, colon and liver, and this has been attributed to its phytochemical profile, mainly its phenolic compounds. This study aimed to evaluate the cytotoxicity and antiproliferative potential of the polyphenols-rich extracts (PRE) of the oregano species H. patens, L. graveolens, and L. palmeri on breast cancer cell lines. The PRE of the three oregano species were obtained from dried leaves. The extract was characterized by determining antioxidant activity, total phenols content, and identifying the profile of phenolic acids and flavonoids by chromatography UPLC-MS/MS. Furthermore, the cytotoxicity of the extracts was evaluated in vitro on a non-cancer cell line of fibroblast NIH3T3 and the antiproliferative potential on the breast cancer cell lines MDA-MB-231 and MCF-7. L. graveolens showed the highest antioxidant capacity and significantly inhibited the proliferation of MCF-7 and MDA-MB-231 cells at non-cytotoxic concentrations in normal cells, with a similar effect to that cisplatin in MDA-MB-231 cells. Therefore, the polyphenol-rich extract from L. graveolens showed the greatest potential to guide future research on the antiproliferative mechanism of action.
Microstructured Optical Fibers Based Hybrid Fabry–Perot Interferometer Structure for Improved Strain Sensing by Vernier Effect

We present a novel strain sensor based on a hybrid Fabry–Perot interferometer (HFPI), which is mainly constructed by a cascade of a suspended-core fiber (SCF) and a hollow-core fiber (HOF) between two single-mode fibers (SMFs). When the optical path length (OPL) is matched to some extent, the reflection spectrum of the proposed HFPI demonstrates dense periodic Fabry–Perot interferometer (FPI) fringes tailored with a widely expanded envelope, the dip or peak of which responds swiftly to the strain due to the Vernier effect and the strain response difference between the SCF and the HOF. Through optimizing the parameters, one can achieve a magnified strain sensitivity up to −91.41 pm/ $\mu \varepsilon $ ranging from 0 to $1800~\mu \varepsilon $ . The strain sensitivity is much higher than that of the single HOF FPI structure or the single SCF FPI structure. Moreover, a theoretical model has been established to explain the principle of the proposed HFPI based on the Vernier effect and the ways to further improve the sensitivity. By adding a fiber Bragg grating (FBG), the temperature can also be interrogated by demodulating the envelope peak of the HFPI and the peak of the FBG. The proposed structure has the advantages of high sensitivity, large dynamic range, temperature discrimination ability, and compact size, providing potential from personal human health perception to public structure health monitoring.
Do or Die: Analysis of Bankruptcy Risk from a Research and Development Perspective

ABSTRACT Arguably, R&D remains one of the main drivers for signaling, and its essence in reducing bankruptcy risk (BR) is critical. We revisit the literature and debate and find that since 1982, R&D investment has, on average, been increasing at an annual rate of 0.033%, while BR has been decreasing at an annual rate of 9.02%. Empirically, we find consistent evidence that R&D investment reduces BR. Also, firms with a higher likelihood of bankruptcy have a higher marginal benefit from incremental investment in R&D. Additional results suggest that capital structure and other signaling strategies matter in how R&D affects BR.
Potential Gonado-Protective Effect of Cichorium endivia and Its Major Phenolic Acids against Methotrexate-Induced Testicular Injury in Mice

Cichorium endivia L. (Asteraceae) is a wide edible plant that grows in the Mediterranean region. In this study, a phytochemical investigation of C. endivia L. ethanolic extract led to the isolation of stigmasterol (1), ursolic acid (2), β-amyrin (3), azelaic acid (4), vanillic acid (5), (6S, 7E)-6-hydroxy-4,7-megastigmadien-3,9-dione (S(+)-dehydrovomifoliol) (6), 4-hydroxy phenyl acetic acid (7), vomifoliol (8), ferulic acid (9), protocatechuic acid (10), kaempferol (11), p. coumaric acid (12), and luteolin (13). In addition, the total phenolic content as well as the in vitro antioxidant activity of C. endivia L. extract were estimated. Moreover, we inspected the potential gonado-protective effect of C. endivia crude extract, its phenolic fraction, and the isolated coumaric, vanillic, and ferulic acids against methotrexate (MTX)-induced testicular injury in mice. There were seven groups: normal control, MTX control, MTX + C. endivia crude extract, MTX + C. endivia phenolic fraction, MTX + isolated coumaric acid, MTX + isolated vanillic acid, and MTX + isolated ferulic acid. MTX was given by i.p. injection of a 20 mg/kg single dose. The crude extract and phenolic fraction were given with a dose of 100 mg/kg/day, whereas the compounds were given at a dose of 10 mg/kg/day. A histopathological examination was done. The testosterone level was detected in serum together with the testicular content of malondialdehyde (MDA), catalase (CAT), superoxide dismutase (SOD), interleukin 1β (IL-1β), IL-6, tumor necrosis factor alpha (TNF-α), nuclear factor kappa B (NF-κB), B-cell lymphoma 2 (Bcl-2), Bcl-2 associated x protein (Bax), p53, and miR-29a. C. endivia crude extract, the phenolic fraction, and the isolated compounds showed significant elevation in their levels of testosterone, CAT, SOD, Bcl-2 with a significant decrease in their levels of MDA, TNF-α, IL-1β, IL-6, NF-κB, Bax, P53, and miR-29a compared to those of the MTX control group. In conclusion, C. endivia mitigated MTX-induced germ cell toxicity via anti-inflammatory, antioxidant, and antiapoptotic effects.
Surveying the Landscape of Professional Development Research: Suggestions for New Perspectives in Design and Research

ABSTRACT Science, technology, engineering, and mathematics (STEM) higher education is in need of improved teaching methods to increase learning for all students. Faculty professional development programs are a widespread strategy for fostering this improvement. Studies of faculty development programs have focused on program design and the impact of surrounding context, including both social supports for learning and institutional context. I reviewed these approaches, as well as work that focused on the faculty experience, and suggest that a larger perspective that encompasses learning over time and the interactions between disciplinary and institutional learning opportunities is important. This leads to both new design considerations and new research questions that focus on increasing faculty skill in learning about teaching and applying the results, as well as improving the impact of professional development beyond the immediate participants.
An Analysis of Vocal Features for Parkinson’s Disease Classification Using Evolutionary Algorithms

Parkinson’s Disease (PD) is a brain disorder that causes uncontrollable movements. According to estimation, roughly ten million individuals worldwide have had or are developing PD. This disorder can have severe consequences that affect the patient’s daily life. Therefore, several previous works have worked on PD detection. Automatic Parkinson’s Disease detection in voice recordings can be an innovation compared to other costly methods of ruling out examinations since the nature of this disease is unpredictable and non-curable. Analyzing the collected vocal records will detect essential patterns, and timely recommendations on appropriate treatments will be extremely helpful. This research proposed a machine learning-based approach for classifying healthy people from people with the disease utilizing Grey Wolf Optimization (GWO) for feature selection, along with Light Gradient Boosted Machine (LGBM) to optimize the model performance. The proposed method shows highly competitive results and has the ability to be developed further and implemented in a real-world setting.
Efficacy of Parenting Programs to Reduce Parenting Burdens in Multicultural Families: A Systematic Review and Meta-Analysis

Background: We comprehensively investigated and summarized the current situation of parenting programs for multicultural families in South Korea. Methods: Two researchers independently searched and selected 16 studies on parenting programs for multicultural families and analyzed the major dependent variables, including parenting stress, parenting efficacy, parenting attitude, and parental satisfaction, in a meta-analysis of parenting stress and parenting efficacy (n=6 each). This study was dealt with a Bayesian meta-analysis to perform examine the effect sizes for parenting stress and parenting efficacy. Sensitivity to prior distributions was evaluated before the Bayesian meta-analysis, and an optimal prior distribution was selected based on the Watanabe–Akaike information criterion. Results: The combined effect sizes for parenting stress and parenting efficacy were found to be >1 in both the frequentist and Bayesian meta-analyses, indicating that the parenting programs for multicultural families in South Korea are highly effective. Conclusion: These basic data can facilitate the expansion of customized social services for reducing parenting burdens in multicultural families.
Optimization Strategy Analysis of Intelligent Product Service System Based on Computer Simulation Technology

In order to solve the needs of a large number of users and the efficiency of user service requirements, an optimization strategy analysis method of intelligent product service system based on computer simulation technology is proposed. Aiming at the two challenges of massive requests and efficient service in the network intelligent service system, the characteristics of the network intelligent service system are analyzed, and the network intelligent service system is formally modeled as an agent system. The performance modeling, performance evaluation, and performance optimization methods of the network intelligent service system are proposed. In order to solve this massive demand, the performance modeling of the network intelligent service system is carried out based on queuing theory. This paper proposes a task assignment algorithm for the network intelligent service system. Through the application of these results, the processing efficiency of the entire medical insurance application system has been greatly improved, and the average completion time of all businesses has been shortened by 59%, providing new ideas for optimizing service methods and improving service quality.
Investigating Hot-Carrier Degradation in MOSFETs using Constant and Switched Biased Low-Frequency Noise measurements

Periodically switching the MOSFET ‘off’ (switched biasing), is known to reduce the low-frequency (LF) noise power spectrum. In this work, the constant and switched biased LF noise has been measured on devices before and after hot-carrier stress. The switched biased LF noise is more sensitive to hot-carrier degradation than the constant biased LF noise. The anomalous noise reduction, due to switched biasing, observed for fresh devices, gradually disappears as the devices are subjected to hot-carrier stress. Devices with a deuterium passivated SiO2/Si interface degrade significantly slower, as seen from our LF noise measurements.
A Survey on Intelligent Gesture Recognition Techniques

Gesture recognition is an ideal means of interaction because it allows users not to have to make contact with any surface, which is a safe and hygienic means, especially in the pandemic situation that is occurring worldwide. However, gesture recognition is not a new discipline and it has been researched for many years but this type of interaction has not succeeded in replacing the keyboard and mouse. It is very useful to know about the advances that are being made with artificial intelligence in gesture recognition to be able to perform a more robust and reliable gesture recognition with a low response time. As it is, deep learning is being integrated into various areas to increase improvement in performance and one such area is artificial intelligence. In this way, there is the possibility that in the future the recognition of gestures will be a viable option as a means of daily interaction for the user and the main objective of this paper is to contribute to that process. For this reason, this study has analyzed 571 papers related to gesture recognition and artificial intelligence. This analysis has extracted relevant information related to scientific production, such as the most productive authors and journals or the most pertinent articles on the subject. Furthermore, we have developed our own model, which shows the relationship between the types of gesture recognition and the artificial intelligence techniques that have been applied for this task.
Heat stress exposure changed liver lipid metabolism and abdominal fat deposition in broilers

Abstract To evaluate the effects of heat stress on lipid metabolism in the liver and abdominal adipose deposition in broilers, totally, 120 female 21-day old broilers were selected and randomly allocated to 2 groups with 6 replication and 10 broilers per each replication. Broilers in the control group (CON) were reared at 24 °C, and broilers in the heat stress group (HS) were reared at 34 °C. Heat stress exposure increased (P < 0.05) rectal temperature, relative weight of abdominal adipose and liver, serum triacylglycerol (TG) and total cholesterol (TC) level, liver TG, TC, and very low-density lipoprotein (VLDL) content. Hepatic mRNA expression level of fatty acid synthase (FAS), acetyl-coenzyme A carboxylase (ACC), and abdominal adipose mRNA expression level of ACC and CCAAT/enhancer-binding protein-α (C/EBPα) were up-regulated (P < 0.05) when compared with the CON group. Heat stress exposure increased serum and hepatic TC and TG content, up-regulated the mRNA expression of FAS and ACC in liver, and promoted preadipocytes differentiation by increasing C/EBPα mRNA expression in abdominal adipose. Therefore, heat stress exposure increased abdominal adipose deposition, which related to increase in hepatic de novo lipogenesis, and promoted preadipocytes differentiation in abdominal adipose. HIGHLIGHTS Heat stress increased abdominal adipose deposition Heat stress increased hepatic de novo lipogenesis Heat stress promoted preadipocytes differentiation in abdominal adipose
Dl-3-n-Butylphthalide Reduced Neuroinflammation by Inhibiting Inflammasome in Microglia in Mice after Middle Cerebral Artery Occlusion

The inflammatory response is one of the key events in cerebral ischemia, causing secondary brain injury and neuronal death. Studies have shown that the NLRP3 inflammasome is a key factor in initiating the inflammatory response and that Dl-3-n-butylphthalide (NBP) can attenuate the inflammatory response and improve neuronal repair during ischemic stroke. However, whether NBP attenuates the inflammatory response via inhibition of NLRP3 remains unclear. A 90 min middle cerebral artery occlusion was induced in 62 2-month-old adult male ICR mice, and NBP was administered by gavage zero, one, or two days after ischemia. Brain infarct volume, neurological deficits, NLRP3, microglia, and neuronal death were examined in sacrificed mice to explore the correction between NBP effects and NLRP3 expression. NBP significantly reduced infarct volume and attenuated neurological deficits after ischemic stroke compared to controls (p < 0.05). Moreover, it inhibited ASC+ microglia activation and NLRP3 and CASP1 expression in ischemic mice. In addition, neuronal apoptosis was reduced in NBP-treated microglia cultures (p < 0.05). Our results indicate that NBP attenuates the inflammatory response in ischemic mouse brains, suggesting that NBP protects against microglia activation via the NLRP3 inflammasome.
RF Power Transfer, Energy Harvesting, and Power Management Strategies

Energy harvesting is the way to capture green energy. This can be thought of as a recycling process where energy is converted from one form (here, non-electrical) to another (here, electrical). This is done on the large energy scale as well as low energy scale. The former can enable sustainable operation of facilities, while the latter can have a significant impact on the problems of energy constrained portable applications. Different energy sources can be complementary to one another and combining multiple-source is of great importance. In particular, RF energy harvesting is a natural choice for the portable applications. There are many advantages, such as cordless operation and light-weight. Moreover, the needed infra-structure can possibly be incorporated with wearable and portable devices. RF energy harvesting is an enabling key player for Internet of Things technology. The RF energy harvesting systems consist of external antennas, LC matching networks, RF rectifiers for ac to dc conversion, and sometimes power management. Moreover, combining different energy harvesting sources is essential for robustness and sustainability. Wireless power transfer has recently been applied for battery charging of portable devices. This charging process impacts the daily experience of every human who uses electronic applications. Instead of having many types of cumbersome cords and many different standards while the users are responsible to connect periodically to ac outlets, the new approach is to have the transmitters ready in the near region and can transfer power wirelessly to the devices whenever needed. Wireless power transfer consists of a dc to ac conversion transmitter, coupled inductors between transmitter and receiver, and an ac to dc conversion receiver. Alternative far field operation is still tested for health issues. So, the focus in this study is on near field. The goals of this study are to investigate the possibilities of RF energy harvesting from