Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation with Correctly Interpreted Dummy Variables in Semilogarithmic Equations

A recent note in this journal by Robert Halvorsen and Raymond Palmquist pointed out that empirical studies using a semilogarithmic functional form with dummy variables had misinterpreted the estimates of the coefficients of the dummy variables. For c, the estimate of a dummy variable coefficient c, it has been common practice to estimate the percentage effect of that dummy variable on the variable being explained by 1OOc'. Halvorsen and Palmquist show that c is in fact an estimate of c=ln(1 +g) where lOOg is the correct measure of the percentage impact of the dummy variable on the variable being explained. Unfortunately, Halvorsen and Palmquist address only the question of the relationship between c and g, ignoring the important problem of how c should be used to estimate g. They implicitly lead readers to believe that g should be estimated by g=exp(c)1, a biased estimator. This can be defended on the grounds that if c is a consistent estimate of c then g will be a consistent estimate of g; for those willing to defend estimates on asymptotic grounds, however, this estimate may not be acceptable. Suppose, as is customary, that the error term in the original specification is lognormally distributed, and that c is an unbiased estimate of c. Then as noted by Arthur Goldberger, E exp(c) = exp(c+ 2 V(C)) where V(c) is the variance of c'. This suggests estimating exp(c) by exp(cV(C)) where V(c) is an estimate of the variance of c'. This implies an estimate for g of
Transmission Optimization and Resource Allocation for Wireless Powered Dense Vehicle Area Network With Energy Recycling

The wireless-powered communication paradigm brings self-sustainability to the on-vehicle sensors by harvesting the energy from radiated radio frequency (RF) signals. This paper proposes a novel transmission and resource allocation strategy for the scenario where multiple wireless powered vehicle area networks (VAN) co-existed with high density. The considered multi-VAN system consists of a remote master access point (MAP), multiple on-vehicle hybrid access points (HAPs) and sensors. Unlike previous works, we consider that the sensors can recycle the radiated radio frequency energy from all the HAPs when HAPs communicate with MAP, so the dedicated signals for energy harvesting (EH) are unnecessary. The proposed strategy can achieve simultaneous wireless information and power transfer (SWIPT) without complex receiver architecture requirements. The extra EH and interference caused by the dense distribution of VANs, which are rarely explored, are fully considered. To maximize the sum throughput of all the sensors while guaranteeing the transmission from HAPs to the MAP, we jointly optimize the time allocation, system energy consumption, power allocation, and receive beamforming. Due to the non-convexity of the formulated problem, we address the sub-problems separately through the Rayleigh quotient, Frobenius norm minimization and convex optimization. Then an efficient iterative algorithm to obtain sub-optimal solutions. The simulation results and discussions illustrate the proposed scheme's effectiveness and advantages.
Multi-scale modeling of flow and transport processes in arterial networks and tissue

This thesis is concerned with the simulation of blood flow and mass transport in vascularized human tissue. Our mathematical model is based on a domain decomposition approach, i.e., we separate the blood vessel network from the tissue and assign different flow and transport models to them. To simulate the transfer between the blood vessels and the tissue, appropriate coupling conditions are designed. The performance of our model is illustrated by some applications from bio-mechanics.
A color channel multiplexing approach for robust discrete wavelet transform based image watermarking

Copyright protection of digital images has become a consequential issue in recent years. To prevent a breach of copyright for a color image, this article presents a novel discrete wavelet transform (DWT) based robust image watermarking method with a color channel multiplexing approach. In this proposed method, the original color image is separated into red, green, and blue color channels. One of these color channels is copied and a set of four channels is obtained. Then these channels are combined to obtain a new gray‐level cover image. 2‐level DWT is performed on the cover image. Arnold scrambled binary watermark image i embedded into the low‐frequency sub‐band of the cover image. 2‐level inverse DWT is performed to produce a gray‐level watermarked image. Then a demultiplexing process is performed by separating the gray‐level watermarked image into four color channels. The average values of the two copied color channels are calculated and then converted into a single‐color channel. Finally, the watermarked color image is get by merging three different color channels. To approve the performance of the presented method, various experimental tests have been performed and a benchmarking analysis has been conducted. The results show that the proposed method is robust against non‐linear and linear attacks while protecting watermarking imperceptibility.
A PFC Power Supply with Minimized Energy Storage Components and a New Control Ttechnique for Cascaded SMPS

A PFC power supply with minimized energy storage components and a new control technique for cascaded SMPS Damien F. Frost Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2009 This Master of Applied Science thesis proposes a new design of low power, power factor corrected (PFC), power supplies. By lifting the hold up time restriction for devices that have a battery built in, the energy storage elements of the converter can be reduced, permitting a small and inexpensive power converter to be built. In addition, a new control technique for controlling cascaded converters is presented, named duty mode control (DMC). Its advantages are shown through simulations. The system was proven using a prototype developed in the laboratory designed for a universal ac input voltage (85 265VRMS at 50 60Hz) and a 40W output at 12V . It consisted of two interleaved phases sensed and digitally controlled on the isolated side of the converter. The prototype was able to achieve a power factor of greater than 0.98 for all operating conditions, and input harmonic current distortion well below any set of standards.
Smart specialization and participatory processes in green path renewal. Analysis of the forest-based bioeconomy in sparsely populated regions in the Nordics

ABSTRACT This paper examines two atypical sparsely populated regions and their experience implementing a strategy of forest-based bioeconomy through smart specialization. Smart specialization is increasingly promoted as an opportunity for green transformations. Indeed, its recent evolution from S3 to S4 is an effort to address environmental sustainability challenges alongside regional development. In this paper, we argue that one of smart specialization’s early stages, the entrepreneurial discovery process (EDP), can help establish a basis for the green transformation of traditional industries located in sparsely populated areas. The EDP is a participatory process that gathers diverse actors interested in developing a common economic sector, mostly through innovation. We explain how multi-actor participation facilitate understanding innovation as a problem-solving process requiring the input of actors outside (but including) the firms. As the cases show, this can unlock the potential of place-based multi-actor interventions to identify and mobilize pre-existing conditions and resources that, when combined with a common agenda, can influence green path renewal. In our cases, those pre-existing conditions are a culture of collaboration, knowledge, infrastructure and access to natural resources. The common agenda is to transform the regional economy into a forest-based bioeconomy.
Balanced liquid metal reconfigurable microstrip filter

Abstract A reconfigurable balanced resonator and a reconfigurable Balanced Band-Pass Filter (BBPF) are presented in this work. The resonator is based on closed-loop transmission lines, two parallel lines and two T-sections. Reconfigurability is achieved using Eutetic Galium–Indium (EGaIn) liquid metal. A third-order reconfigurable filter was designed, fabricated, and measured to work at 2 and 1.65 GHz.
An Improved Control Method for Power Conversion System under a Weak Grid by the Adoption of Virtual Resistors

The control of the power conversion system (PCS) in a battery energy storage system has a challenge due to the existence of grid impedance. This paper studies an impedance model of an LCL-based PCS in the d-q domain. The feature of a PCS connected to a weak grid is unveiled by use of an impedance model and a generalized Nyquist criterion. It is shown that the interaction between grid impedance and the PCS destabilizes the cascaded system in certain cases. Therefore, this paper proposes a novel control method that adopts virtual resistors to overcome this issue. The improvement in the control loop leads the PCS to a more stable condition than the conventional method. Impedance measurement is implemented to verify the correctness of the theoretical analysis. Experimental results obtained from a down-scaled prototype indicate that the proposed control method can improve the performance of the PCS under a weak grid.
Determinants of Health-Related Quality of Life among Post-Partum Women Residing in a Resettlement Colony of East Delhi.

Abstract: The postpartum period marks a transition phase in the life of the mother as well as the whole family. Health Related Quality of Life (HRQoL) is an important aspect for not only mother’s physical and psychological health. The study was conducted in a resettlement colony, Kalyanpuri located in Delhi, India with a sample size of 330 post-partum women and the data was collected in the 6th week of post-partum period using the MOS SF-36 (Medical Outcomes Study Short Form 36 Health Survey) for health related quality of life. Among the study subjects, 34.2% had the birth order two and they showed the best mean HRQoL score. The mean score was low for the study subjects with complications in the antepartum, intrapartum and postpartum period (52.9 ± 18.4) as well as in foetal complications where the intrapartum period complications had the worst mean HRQoL score. Healthcare workers of the study area visited 91.5% of the subjects during the post-partum period and had better HRQoL mean score. Also, 22.4% subjects had history of mistreatment and abuse with decline in the mean HRQoL scores. Across the study subjects, 54.4% had financial hardships faced by their family members which had poor HRQoL mean scores. This study uncovered various horizons of health related quality of life for assessment of women in the post-partum period which emphasised the modifications and considerations to include quality as one of the determinant and indicator of health.
A Study of Sentiment Analysis Algorithms for Agricultural Product Reviews Based on Improved BERT Model

With the rise of mobile social networks, an increasing number of consumers are shopping through Internet platforms. The information asymmetry between consumers and producers has caused producers to misjudge the positioning of agricultural products in the market and damaged the interests of consumers. This imbalance between supply and demand is detrimental to the development of the agricultural market. Sentiment tendency analysis of after-sale reviews of agricultural products on the Internet could effectively help consumers evaluate the quality of agricultural products and help enterprises optimize and upgrade their products. Targeting problems such as non-standard expressions and sparse features in agricultural product reviews, this paper proposes a sentiment analysis algorithm based on an improved Bidirectional Encoder Representations from Transformers (BERT) model with symmetrical structure to obtain sentence-level feature vectors of agricultural product evaluations containing complete semantic information. Specifically, we propose a recognition method based on speech rules to identify the emotional tendencies of consumers when evaluating agricultural products and extract consumer demand for agricultural product attributes from online reviews. Our results showed that the F1 value of the trained model reached 89.86% on the test set, which is an increase of 7.05 compared with that of the original BERT model. The agricultural evaluation classification algorithm proposed in this paper could efficiently determine the emotion expressed by the text, which helps to further analyze network evaluation data, extract effective information, and realize the visualization of emotion.
Potency of bacterial sialidase Clostridium perfringens as antiviral of Newcastle disease infections using embryonated chicken egg in ovo model

Background and Aim: Clostridium toxins are widely used as medicinal agents. Many active metabolic enzymes, including sialidase (neuraminidase), hyaluronidase, and collagenase, contribute to the mechanism of action of these toxins. Sialidase from Clostridium perfringens recognizes and degrades sialic acid receptors in the host cell glycoprotein, glycolipid, and polysaccharide complexes. Sialic acid promotes the adhesion of various pathogens, including viruses, under pathological conditions. This study aimed to investigate the potential of C. perfringens sialidase protein to inhibit Newcastle disease virus (NDV) infection in ovo model. Materials and Methods: C. perfringens was characterized by molecular identification through polymerase chain reaction (PCR) and is cultured in a broth medium to produce sialidase. In addition, sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis was conducted to characterize the sialidase protein. In contrast, enzymatic activity and protein concentration were carried out using a neuraminidase assay kit and Bradford to obtain suitable active substances. Furthermore, embryonated chicken egg models were used to observe the toxicity of several sialidase doses. Then, the hemagglutination (HA) titer was obtained, and absolute quantitative reverse transcription–PCR assay was performed to measure the viral replication inhibitory activity of sialidase against NDV. Results: Each isolate had a specific sialidase gene and its product. The sialidase derived from C. perfringens could hydrolyze the sialic acid receptor Neu5Ac (2,6)-Gal higher than Neu5Ac (2,3)Gal in chicken erythrocytes, as observed by enzyme-linked lectin assay. A significant difference (p = 0.05) in the HA titer in the pre-challenge administration group at dosages of 375 mU, 187.5 mU, and 93.75 mU in the competitive inhibition experiment suggests that sialidase inhibits NDV reproduction. Quantification of infective viral copy confirmed the interference of viral replication in the pre-challenge administration group, with a significant difference (p = 0.05) at the treatment doses of 750 mU, 375 mU, and 46.87 mU. Conclusion: The potency of sialidase obtained from C. perfringens was shown in this study, given its ability to reduce the viral titer and copy number in allantoic fluids without adversely impacting the toxicity of the chicken embryo at different concentrations.
Positive association of unhealthy plant-based diets with the incidence of abdominal obesity in Korea: a comparison of baseline, most recent, and cumulative average diets

OBJECTIVES Different approaches for analyzing repeated dietary measurements may yield differences in the magnitude and interpretation of findings. We aimed to compare 3 dietary measurements (baseline, most recent, and cumulative average) in terms of the association between plant-based diet indices (PDIs) and incident abdominal obesity in Korean adults aged 40-69 years. METHODS This study included 6,054 participants (54% women) free of abdominal obesity (defined as waist circumference ≥90 cm for men and ≥85 cm for women) at baseline. As exposures, baseline, most recent, and cumulative average measurements for PDI, healthy-PDI (hPDI), and unhealthy-PDI (uPDI) were created. A Cox proportional-hazard model was used to estimate the hazard ratios (HRs) for abdominal obesity. RESULTS During 45,818 person-years of follow-up (median, 9 years), we identified 1,778 incident cases of abdominal obesity. In the multivariable-adjusted analysis, a higher uPDI was associated with a higher risk of abdominal obesity in both total and stratified analyses. The findings were consistent across all approaches (Q5 vs. Q1: HRbaseline=1.70; 95% confidence interval [CI], 1.46 to 1.98; HRmost recent=1.52; 95% CI, 1.30 to 1.78; HRcumulative average=1.76; 95% CI, 1.51 to 2.06 in the total set). PDI showed no meaningful association with abdominal obesity risk in any analyses. HRaverage had a suggestive inverse association with abdominal obesity risk in men, and hPDIbaseline had a positive association with abdominal obesity risk in women. CONCLUSIONS Greater adherence to unhealthy plant-based diets may increase the risk of developing abdominal obesity in Korean adults. The findings were generally consistent across all approaches.
Study on Early Warning of Karst Collapse Based on the BP Neural Network

In order to comprehensively grasp the dynamics of karst collapse, promote the comprehensive prevention and control level of karst collapse, and prevent secondary disasters caused by lava collapse, this study presents a method of karst collapse early warning based on the BP neural network. This method does not need to set the sliding surface in the finite element calculation model. The stress of the sliding surface is fitted according to the spatial stress relationship of the deep karst layer through the improved BP neural network PID control algorithm and BP neural network algorithm, which avoids the modeling and mesh generation of the complex sliding block and has good accuracy and ease of use. According to the basic theory of the BP neural network, the calculation formulas of multilayer feedforward and error back propagation processes are derived, and the two-dimensional and three-dimensional finite element models of gravity dams without and with sliding blocks are established, respectively. Finally, according to the common formulas of viscoelastic artificial boundary and equivalent load, the two-dimensional and three-dimensional input programs of the karst fluid state are compiled, and a neural network early warning model is obtained. The experimental results show that the process karst state simulated by the algorithm is very close to the actual situation, and the minimum value of antisliding coefficient and its occurrence time can be accurately predicted, with an error range of less than 3%. Conclusion. BP neural network prediction can effectively predict karst collapse, with higher prediction accuracy, and can effectively simulate the actual collapse risk.
Modeling of NOMA-MIMO-Based Power Domain for 5G Network under Selective Rayleigh Fading Channels

The integration of multiple-input multiple-output (MIMO) and non-orthogonal multiple access (NOMA) technologies is a hybrid technology that overcomes a myriad of problems in the 5G cellular system and beyond, including massive connectivity, low latency, and high dependability. The goal of this paper is to improve and reassess the bit error rate (BER), spectrum efficiency (SE) of the downlink (DL), average capacity rate, and outage probability (OP) of the uplink (UL) in a 5G network using MIMO. The proposed model utilizes QPSK modulation, four users with different power location coefficients, SNR, transmit power, and two contrasting bandwidths 80 and 200 MHz under selective frequency Rayleigh fading channels. The proposed model’s performance is evaluated using the MATLAB software program. The DL results found that the BER and SE against transmitted power showed the MIMO-NOMA enhanced the BER performance for the best user U4 from 10−1.7 to 10−5.2 at 80 MHz bandwidth (BW), and from 10−1.5 to 10−5 at 200 MHz for transmitting power of 40 dBm. In contrast, the SE performance for the best user U4 is enhanced from 24 × 10−3 to 25 × 10−3 bits/second/Hz at 80 MHz BW and from 19.8 × 10−3 to 20 × 10−3 bps/Hz at 200 MHz BW. Although the outcomes for the UL were obtained in terms of average capacity rate and OP versus SNR at 80, and 200 MHz BW, the MIMO-NOMA result showed that the average capacity rate for the best user U4 performance improves by 12 bps/Hz for 1 dB SNR and the OP is reduced by 15 × 10−3 for 80 MHz BW and by 12 × 10−3 for 200 MHz BW at an SNR of 0.17 dB. As the BW increased the BER, the average capacity rate increased while the SE and OP decreased. For both DL/UL NOMA with and without MIMO, closed-form expressions for BER, SE, average capacity rate, and OP were obtained. All users’ performance, even those whose connections were affected by interference or Rayleigh fading channels significantly improved, when MIMO-NOMA was implemented.
A framework for predicting consumers’ sustainable purchase in COVID era

The pandemic generated by the outbreak of the coronavirus disease (COVID-19) has had a major impact on individual behavior in general and on consumption choices in specific, as people started to pay more attention to the balance between human and nature and shift to healthier, environmental and nutritional sustainable products (such as organic food). However, the organic food market is still relatively small in size at present, especially in developing countries like Egypt. the guaranteeing
Metabolic Pathways as a Novel Landscape in Pancreatic Ductal Adenocarcinoma

Simple Summary The survival of organic systems is dependent on metabolic conditions, necessary for the proper functioning of all biological processes. Cancer takes advantage of altered bioenergetic circuits to improve its chances of growth, and pancreatic ductal adenocarcinoma is no exception. In this review, we describe the metabolic features of pancreatic ductal adenocarcinoma and discuss how this dependency could be exploited as a weakness for clinical interventions. Abstract Metabolism plays a fundamental role in both human physiology and pathology, including pancreatic ductal adenocarcinoma (PDAC) and other tumors. Anabolic and catabolic processes do not only have energetic implications but are tightly associated with other cellular activities, such as DNA duplication, redox reactions, and cell homeostasis. PDAC displays a marked metabolic phenotype and the observed reduction in tumor growth induced by calorie restriction with in vivo models supports the crucial role of metabolism in this cancer type. The aggressiveness of PDAC might, therefore, be reduced by interventions on bioenergetic circuits. In this review, we describe the main metabolic mechanisms involved in PDAC growth and the biological features that may favor its onset and progression within an immunometabolic context. We also discuss the need to bridge the gap between basic research and clinical practice in order to offer alternative therapeutic approaches for PDAC patients in the more immediate future.