Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitochondrial and chloroplast genome sequences of Ulva ohnoi, a green-tide-forming macroalga in the Southern coastal regions of Japan

Abstract Ulva is a green macroalga often causing a macroalgal bloom, ‘green tide’. Ulva ohnoi is a major species composing the green tide of the southern coastal regions of Japan. Here, we sequenced the complete mitochondrial and chloroplast genomes of the authentic strain of U. ohnoi. The mitochondrial and chloroplast genomes were of 65,326 bp and 103,313 bp, respectively, and the gene content was highly conserved in the Ulva species. The phylogenetic analyses using mitochondrial or chloroplast proteins represented the same topology with high supporting values. These results show that mitochondrial and chloroplast genomes can be used as reliable phylogenetic markers.
Search Engine Consumer Journeys: Exploring and Segmenting Click-Through Behaviors

The consumer online search journey is viewed as one of the key determinants toward consumer purchase decisions. Using a unique disaggregated query-level data set collected from a leading Chinese search engine, we employ a latent-class, two-stage logistic regression model and identify the existence of three distinct consumer segments in the hospitality industry. Each group represents a unique stage of the consumer experience along a typical search journey, leading to a set of click-through behaviors. The consumer search and click-through insights garnered from this study provide hotel marketers with deeper understandings and actionable guidelines to the development of their search advertising campaign and (re)targeting strategies. The segmentation model and the empirical insights also demonstrate the possibility that a segment-specific ad assortment approach could improve advertising efficiency, enrich consumer’s search experience, and eventually create a win-win situation that benefit all entities involved in the hospitality-related, search advertising domain.
Recommendations for policy and practice of telepsychotherapy and e-mental health in Europe and beyond.

The COVID-19 pandemic has brought with it a great need for the use of telepsychotherapy and other interventions using psychological theories and techniques to support both mental and physical health. E-mental health presents a wide range of opportunities in mental health care to overcome barriers for receiving conventional psychological care, especially when psychotherapists and clients find themselves in (self)quarantine resulting from a pandemic. For many psychotherapists and clients, the current situation provides a first experience with e-mental health and reliance on telepsychotherapy or other means of technology to provide or receive care, respectively. Psychotherapeutic circumstances may often be suboptimal, with psychotherapists and clients experiencing difficulties finding a private space or sufficient time for an undisturbed consultation. This article aims to highlight recommendations on how to create the best possible context in which e-mental health supplements and enhances current services for clients. These recommendations are grouped according to 3 categories of key stakeholders: psychotherapists, health services and regulatory agencies, and developers. This article focuses on (a) how to make optimal use of technology in psychotherapeutic practice; (b) how to integrate e-mental health into the health care system to allow for a safe, transparent, and effective environment for (self) care; and (c) how to develop e-mental health applications.
Discrete-Phase Waveform Design to Quadratic Optimization via an ADPM Framework with Convergence Guarantee

This paper considers a quadratic optimization problem in radar discrete-phase waveform design under similarity and constant modulus constraints. A computationally efficient iterative algorithm based on the Alternating Direction Penalty Method (ADPM) framework is proposed. In each iteration, it converts the considered problem into two subproblems with closed-form solutions via an introduced auxiliary variable, while locally increasing the penalty factor involved in the ADPM framework. The proposed algorithm is ensured to converge for any initialization under some mild conditions and avoids the non-convergence problem of the Alternating Direction Method of Multipliers (ADMM) when handling the NP-hard problems. Finally, numerical simulations demonstrate that the proposed algorithm can outperform their counterparts by providing better objective values.
Butylated Hydroxytoluene in Edible Vegetable Oils from Local Markets of Chiang Mai and Mae Hong Son and Its Thermal Stability in Different Cooking Conditions

Butylated hydroxytoluene (BHT) was widely used to protect oxidation and rancidity of food products containing fats and oils since it had high antioxidant activity. In this study, samples of edible vegetable oils from 25 local markets in Chiang Mai province and Mae Hong Son province were determined for BHT contents by gas chromatography-mass spectrometry (GC-MS). Of 18 vegetable oil samples, 3 palm oil samples from the local markets contained BHT in the range of 6.8-86.1 μg/g. The extracts of edible vegetable oil samples had 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity in the range of 7.5 to 75.8% which had gallic acid equivalent and BHT equivalent concentrations in the ranges of 6.5 to 65.9 mg/g and 17.2 to173.0 mg/g, respectively. Three different home-cooking conditions were tested for thermal stability of BHT in the samples of palm oil. It was found that cooking temperatures at 98-100°C by boiling or stir-frying for 1-15 min lost BHT 24-31% in the oil, while deep frying at 200±10°C for 5-15 min showed 46-62% loss of BHT.
The study on the influencing factors of brand awareness of Regional Public Brand of Agricultural products-- based on a baseline survey of 409 consumers in China

The regional public brand of agricultural products is an important type of agricultural product brand. There are many successful examples of such brand in the world. The purpose of this paper is to study the factors influencing consumers' brand awareness of regional public brand of agricultural products. First, reliability, validity and factor analysis were carried out. Then FGLS was carried out for the extracted factors and other variables, and robustness test was carried out with binary Probit and Tobit regression models. The main results are as follows: First, brand influence, brand publicity and product quality all have a positive impact on the consumer awareness of regional public brand of agricultural products; Second, brand influence has an both economic and statistical significant impact on the awareness of regional public brand of agricultural products; Third, there are significant differences between men and women in the awareness of regional public brand of agricultural products.
Aplikasi Pencarian Rute Optimal Jasa Pengiriman Barang Menggunakan Metode Ant Colony Optimization (Studi Kasus: TIKI Kubu Raya)

Semakin tingginya minat masyarakat untuk berbelanja secara online menyebabkan perkembangan perusahaan jasa pengiriman barang semakin pesat. Hal ini berdampak pada peningkatan persaingan antar perusahaan jasa pengiriman barang. Untuk mendapatkan kepercayaan konsumen agar tetap digunakan dalam urusan pengantaran barang, pihak perusahaan pengantaran barang harus dapat menjaga ketepatan waktu dalam pengantaran barang. Penelitian ini ditujukan untuk membantu pihak perusahaan pengiriman barang meminimalisir keterlambatan waktu penerimaan barang oleh konsumen dengan membangun aplikasi yang dapat membantu menentukan rute optimal dalam mengantarkan barang. Aplikasi dibangun pada perangkat android dengan mengimplementasikan metode Ant Colony Optimization untuk mendapatkan rute yang optimal. Aplikasi memberikan informasi rute optimal dalam bentuk urutan pengantaran barang yang memiliki jarak tempuh yang paling optimal. Berdasarkan pengujian yang telah dilakukan pada 30 lokasi pengantaran barang, aplikasi menghasilkan urutan rute optimal pengantaran barang dengan total jarak 21.1 km
Target Detection Based on Canonical Correlation Technique for Large Array MIMO Radar in Spatially Correlated Noise

A novel target detection algorithm for large array multi-input multi-output (MIMO) radar in spatially correlated noise is proposed in this paper using canonical correlation technique (CCT). In the signal model, two separate sub-arrays are employed as the receive array of a transmit diversity MIMO radar system. Assume that the elementary noise in each sub-array has spatial correlation, and the number of receive elements is large and grows as the same rate with the snapshots. The detection statistics is constructed based on the generalized likelihood ratio test (GLRT) criterion and the sample canonical correlation coefficient between the two subarrays. The expression of decision threshold is derived via the Tracy-Widom distribution of order 2 in random matrix theory. The simulation results show that the detection performance of the proposed algorithm is better than that of the conventional condition number (CN)-based algorithm in the presence of spatially correlated noise and large array.
Performance Improvement of Clustering Affinity Propagation Method using Principal Component Analysis

Affinity Propagation Method it is necessary to modify the algorithm by using Principal Component Analysis (PCA). PCA method is used to reduce the attributes or characteristics that are less influential on the data so that the most influential attributes are obtained to then be carried out the clustering process with Affinity Propagation. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when there are 8 optimal cluster clusters. While the performance of conventional clustering models produces an optimal number of clusters from 14 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Air Quality dataset because it produces an optimal number of clusters and iterations of 8 clusters. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when the optimal number of clusters is 5 clusters. While the performance of conventional clustering models produces a suboptimal number of 10 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Water Quality Status dataset because it produces an optimal number of clusters and 5 cluster repetitions.
Transient Response of High Dimensional Nonlinear Dynamic System for a Rotating Cantilever Twisted Plate

Dynamic transient responses of rotating twisted plate under the air-blast loading and step loading respectively considering the geometric nonlinear relationships are investigated using classical shallow shell theory. By applying energy principle, a novel high dimensional nonlinear dynamic system of the rotating cantilever twisted plate is derived for the first time. The use of variable mode functions by polynomial functions according to the twist angles and geometric of the plate makes it more accurate to describe the dynamic system than that using the classic cantilever beam functions and the free-free beam functions. The comparison researches are carried out between the present results and other literatures to validate present model, formulation and computer process. Equations of motion describing the transient high dimensional nonlinear dynamic response are reduced to a four degree of freedom dynamic system which expressed by out-plane displacement. The effects of twisted angle, stagger angle, rotation speed, load intensity and viscous damping on nonlinear dynamic transient responses of the twisted plate have been investigated. It’s important to note that although the homogeneous and isotropic material is applied here, it might be helpful for laminated composite, functionally graded material as long as the equivalent material parameters are obtained. AMS subject classifications: 34A34
Advanced Applications of Biomaterials Based on Alginic Acid

Alginic acid, also known as algin or alginate, is a natural carbohydrate, which is derived from marine brown algae, as well as some micro- organisms. It can be used in various applications. In particular, alginate has shown great potential in the areas of wound healing, drug delivery, in vitro cell culture, and tissue engineering, allowing the categorization of it as a promising biomaterial, or a basic component of other biomaterials. The unique characteristics of alginic acid, such as the biocompatibility, the mild required gelation conditions, the low toxicity, the relative low cost and the simple modifications, allow the development of alginate hydrogels, and alginate derivatives with enhanced properties. The aim of this review, is to present an overview of the properties of alginate, shedding light on the current and potential applications and suggesting new perspectives for future studies.
Narrative Analysis of The Kurdish Personal Narratives

This study investigates the similarities and difference between the English and Kurdish conversational stories told by Iraqi Kurdish bilingual speakers. Through the quantitative and qualitative analysis of the data (20 hours audio-taped conversational stories told by five Kurdish bilingual speakers in Kurdish and English), the self representation of the Kurdish speakers was examined through emphasizing the ways in which the moral stance dimensions of the personal narratives are enacted in the Kurdish conversational stories by using Labov (1972) and Ochs and Capps’s (2001) models of narrative analysis. The quantitative analysis demonstrates that the Kurdish narrators almost use the same range of the evaluative devices in both the Kurdish and English stories, but that they employ these with a varying extent. This variation has provided the start point to identify the moral positioning by Kurdish bilingual speakers. The moral positioning in this study prompts a range of distancing between the protagonists. The distancing identified was Kurdish-Arabic. This indicated the racial tension between Kurds and Arabs, nominating the Kurdish ethnic identity.
A Histological and Immuno-histchemical study on the Effect of Atorvastatin versus Adipose Derived Stem Cells on Cutaneous Wound Healing in Diabetic Male Albino Rats

AbstractBackground: About 15% of the 150 million people with diabetes worldwide suffer from foot ulcerations, which often become non-healing chronic wounds. Atorvastatin has anti-inflammatory, fibro proliferative, microvascular pleiotropic properties and able to control wound healing process. Adipose-derived stem cells(ADSCs) provide an attractive source of cell therapy for regeneration of damaged skin being able to self-renewal and differentiating into various cells.Aim of the work: To evaluate and compare the effect of atorvastatin versus ADSCs on cutaneous wound healing in diabetic rats. Materials and methods: 85 adult male albino rats one rat for ADSCs preparation and others were divided into six groups each of them was subdivided into subgroups a & b as follow: Subgroup a was sacrificed after 7 days of wounding. Subgroup b was sacrificed after 14 days of wounding. GI control, GII (wounded, non-diabetic rats), GIII (non-treated, wounded diabetic group), GIV (Vaseline and lanoline treated wounded diabetic), GV (ADSCs treated, wounded diabetic rats) injected with single intradermal ADSCs at the edge of the wound one day post wounding. GVI (atorvastatin treated wounded diabetic rats) . Skin specimens were taken from the wound site, processed and stained with H&E, Masson’s trichrome and immunohistochemical stain for vascular endothelial growth factor (VEGF)Results: Wounds of diabetic groups (III &IV) showed delayed healing of wound as compared to the non diabetic group II with failure of re-epithelization and weak to moderate positive VEGF immunoreactions.Whereas, groups treated with atorvastatin or ADSCs exhibited better healing of the wound. However ADSCs group (V) showed better organization of collagen together with reappearance of skin appendages which were missed in atorvastatin group (VI). Conclusion: Both atorvastatin and ADSCs proved a definite ameliorating effect on the wound healing of diabetic rats. However, ADSCs administration denoted a more remarkable therapeutic healing effect compared to Atorvastatin.
Development of Synergetic-Active Sensor-System for Evaluation of Observations by Earthcare

We develop the synergetic ground-based active-sensor-system for the evaluation of observations by space-borne lidars. The system consists of second version of multi-field-view multiple-scattering polarization lidar (MFMSPL-2), multiple-field-of-view high spectral resolution polarization lidar, direct-detection Doppler wind lidar, coherent Doppler wind lidar and 94GHz cloud profiling radar. The system can simulate observed signals from sensors onboard the joint Japanese/European mission Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The observation system can provide unique opportunity to study interaction of cloud microphysics, aerosol microphysics, vertical air motion and vertical distribution of horizontal wind and it will lead to evaluate cloud-convective parameterization and to reduce uncertainties in climate change predictions.
Leader honesty/humility and subordinate organizational citizenship behavior: a case of too-much-of-a-good-thing?

PurposeOn the basis of theories of social cognition and moral identity and the meta-theoretical principle of “too-much-of-a-good-thing,” the purpose of this study is to develop and test a model that explains when and why leader honesty/humility promotes subordinate organizational citizenship behavior directed at individuals (OCBI) as mediated through subordinate moral identity centrality.Design/methodology/approachIn this field study, with online surveys, multisource data were collected from 218 United States Air Force officers and their subordinates. Data were analyzed with MEDCURVE SPSS macro tools.FindingsA nonlinear indirect effect of leader honesty/humility on subordinate OCBI through subordinate moral identity centrality was found. This conditional indirect effect occurred through a curvilinear (inverted U-shape) relationship between leader honesty/humility and subordinate moral identity centrality and a positive linear relationship between subordinate moral identity centrality and OCBI.Research limitations/implicationsCross-sectional data were collected. Future research might replicate findings using experimental and longitudinal designs.Practical implicationsRecruiting and selecting leaders who possess a moderate level of honesty/humility may serve as the first step in producing prosocial behavior during social interactions with subordinates.Originality/valueThis study extends the literature on character and leadership by applying the too-much-of-a-good-thing principle to empirically test the complex nature of the relationship between leader honesty/humility and subordinate OCBI as mediated through subordinate moral identity centrality.
Two-Stage Mask-RCNN Approach for Detecting and Segmenting the Optic Nerve Head, Optic Disc, and Optic Cup in Fundus Images

In this paper, we propose a method for localizing the optic nerve head and segmenting the optic disc/cup in retinal fundus images. The approach is based on a simple two-stage Mask-RCNN compared to sophisticated methods that represent the state-of-the-art in the literature. In the first stage, we detect and crop around the optic nerve head then feed the cropped image as input for the second stage. The second stage network is trained using a weighted loss to produce the final segmentation. To further improve the detection in the first stage, we propose a new fine-tuning strategy by combining the cropping output of the first stage with the original training image to train a new detection network using different scales for the region proposal network anchors. We evaluate the method on Retinal Fundus Images for Glaucoma Analysis (REFUGE), Magrabi, and MESSIDOR datasets. We used the REFUGE training subset to train the models in the proposed method. Our method achieved 0.0430 mean absolute error in the vertical cup-to-disc ratio (MAE vCDR) on the REFUGE test set compared to 0.0414 obtained using complex and multiple ensemble networks methods. The models trained with the proposed method transfer well to datasets outside REFUGE, achieving a MAE vCDR of 0.0785 and 0.077 on MESSIDOR and Magrabi datasets, respectively, without being retrained. In terms of detection accuracy, the proposed new fine-tuning strategy improved the detection rate from 96.7% to 98.04% on MESSIDOR and from 93.6% to 100% on Magrabi datasets compared to the reported detection rates in the literature.
Beneficial Effects of Citrus Flavonoids on Cardiovascular and Metabolic Health

The prevalence of cardiovascular disease (CVD) is increasing over time. CVD is a comorbidity in diabetes and contributes to premature death. Citrus flavonoids possess several biological activities and have emerged as efficient therapeutics for the treatment of CVD. Citrus flavonoids scavenge free radicals, improve glucose tolerance and insulin sensitivity, modulate lipid metabolism and adipocyte differentiation, suppress inflammation and apoptosis, and improve endothelial dysfunction. The intake of citrus flavonoids has been associated with improved cardiovascular outcomes. Although citrus flavonoids exerted multiple beneficial effects, their mechanisms of action are not completely established. In this review, we summarized recent findings and advances in understanding the mechanisms underlying the protective effects of citrus flavonoids against oxidative stress, inflammation, diabetes, dyslipidemia, endothelial dysfunction, and atherosclerosis. Further studies and clinical trials to assess the efficacy and to explore the underlying mechanism(s) of action of citrus flavonoids are recommended.
Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM

Under the influence of the COVID-19 pandemic and the concurrent oil conflict between Russia and Saudi Arabia, oil prices have exhibited unusual and sudden changes. For this reason, the volatilities of the West Texas Intermediate (WTI), Brent and Dubai crude daily oil price data between 29 May 2006 and 31 March 2020 are analysed. Firstly, the presence of chaotic and nonlinear behaviour in the oil prices during the pandemic and the concurrent conflict is investigated by using the Shanon Entropy and Lyapunov exponent tests. The tests show that the oil prices exhibit chaotic behavior. Additionally, the current paper proposes a new hybrid modelling technique derived from the LSTARGARCH (Logistic Smooth Transition Autoregressive Generalised Autoregressive Conditional Heteroskedasticity) model and LSTM (long-short term memory) method to analyse the volatility of oil prices. In the proposed LSTARGARCHLSTM method, GARCH modelling is applied to the crude oil prices in two regimes, where regime transitions are governed with an LSTAR-type smooth transition in both the conditional mean and the conditional variance. Separating the data into two regimes allows the efficient LSTM forecaster to adapt to and exploit the different statistical characteristics and ARCH and GARCH effects in each of the two regimes and yield better prediction performance over the case of its application to all the data. A comparison of our proposed method with the GARCH and LSTARGARCH methods for crude oil price data reveals that our proposed method achieves improved forecasting performance over the others in terms of RMSE (Root Mean Square Error) and MAE (Mean Absolute Error) in the face of the chaotic structure of oil prices.