Miracle-dz/UniFAR-FTUs huggingface dataset:
Commanderella gen. nov. and new insights into foliose Kallymeniaceae (Rhodophyta) from the Russian Pacific coast based on molecular studies

ABSTRACT Molecular analyses of recently acquired sequences from eight specimens from the Russian Pacific region (Kamchatka, Commander Islands and Kurile Islands) reveal necessary taxonomic changes for members of the family Kallymeniaceae: (1) Kallymeniopsis lacera, the generitype, is transferred to Erythrophyllum, resulting in the synonymy of these two genera; K. verrucosa from the Kurile Islands has not been subjected to molecular analyses and remains orphaned and in need of taxonomic study; (2) Velatocarpus is shown to be a distinct genus sister to Erythrophyllum; (3) Hommersandia palmatifolia is sister to Euthora, but is sufficiently genetically and anatomically distinct to continue to be recognised it as a separate genus; and (4) Cirrulicarpus ruprechtianus is resolved as a unique lineage near Metacallophyllis, Pugetia and Salishia and is transferred to a new genus, Commanderella, and the combination C. ruprechtiana (E.S.Sinova) comb. nov. is proposed.
Evaluating a workforce development programme: bringing public health into architecture education in England

ABSTRACT Architects can play a key role in the wider public health workforce, in ensuring building and urban design is health promoting. However, there is no requirement to teach health by architectural accreditation bodies across Europe. To evaluate the long-term individual and organisational impacts of the Public Health Practitioner in Residence (PHPiR) programme – an educational initiative in a British university to help realise the architecture profession’s potential to contribute to improved population health. A longitudinal mixed-methods evaluation using the RE-AIM framework. Data were collected using questionnaires, a focus group, interviews, and programme documentation from a Bachelor of Architecture cohort and stakeholders from 2011 to 2019. Participants developed a broad understanding of the determinants of health, which was maintained when qualified architects. The programme became integrated into the university curriculum. Numerous facilitators and barriers affected the participants’ ability to create healthier buildings in practice. The positive results from this evaluation suggest that there is value in exploring how the PHPiR approach could be replicated in architecture courses within other higher education institutions. Findings highlight barriers in practice to be addressed in the future to help enable architects to create healthier buildings and places.
Object attraction and the role of structural hierarchy: Evidence from Persian

Research on subject-verb agreement production in SVO languages has shown that objects moved pre-verbally sometimes trigger attraction, i.e., erroneous agreement of the verb with the object rather than the subject. Moreover, objects c-commanding one of the agreement positions in the hierarchical structure were found to generate stronger attraction than those linearly preceding them. Evidence for the role of c-command comes from the observation that the accusative clitic in French triggers stronger attraction than the preverbal dative pronoun and the PP modifier (Franck et al. 2006; 2010). In this study, we report the results of an experiment in Persian (an SOV language) in which subject–verb agreement was elicited by presenting sentences in Rapid Serial Visual Presentation procedure (RSVP) followed by verb selection (Staub 2009; 2010). We compared attraction errors induced by pre-verbal accusatives versus datives in the canonical SOV word order as well as the OSV word order. Corroborating Franck et al. (2006; 2010), we found stronger attraction when the pre-verbal object occupies a c-commanding position in the hierarchical structure than when it simply precedes one of the agreement positions in the linear string. We also found stronger attraction in the OSV word order as compared to the canonical SOV word order. This finding is attributed to the real-time processes of erroneous structure building and/or erroneous controller selection during subject-verb agreement computation.
GenPop-An Online Tool to Analyze Human Population Genetic Data

GenPop is a web based online cross platform tool developed to help Geneticist and Epidemiologist to deal with association studies in analyzing human population genetic data. The tool features include descriptive analysis such as Hardy-Weinberg equilibrium test, chi-square p-value and analysis of single nucleotide polymorphisms (SNPs) with multiple inheritance models such as dominant, recessive, allelic, genotype, odd's ratio and relative risk at 95% confidence interval and analysis of multiple SNPs including haplotype frequencies and linkage disequilibrium for a pair of biallelic markers. This is a user-driven human population genetic data analysis tool that is easily scalable and acceptable with multiple implementations of different algorithms. GenPop has been developed using PHP, JavaScript and with PHPExcel library to analyse the genetic data for case control studies.
Molecular dissection of Cdc6 and the miR-148 family : two stories with common themes

This thesis describes the molecular dissection of the function of Cdc6 and the miR-148/152 family. We demonstrate that phosphorylation of the DNA replication initiation protein Cdc6 by CDK2/Cyclin E at serine 54 plays a key role in regulating its protein stability. In response to DNA damage, CDK2/Cyclin E activity will be inhibited, which results in reduced Cdc6 protein level. This regulatory mechanism might prevent initiation of DNA replication in the presence of DNA damage. Loss of p53 results in increased CDK2/cyclin E activity, and our data suggests that the increased stability of Cdc6 in p53 negative cells might be involved in the increased proliferative capacity of these cells. Next we studied several aspects of the miR-148/152 family. We revealed a novel mechanism of miRNA regulation, as we found that Dnmt3b is regulated by miR-148 through interaction with its protein coding region. We studied the function of this miRNA family in more detail in human T-cell development and in cell cycle progression of primary fibroblasts. Theses studies revealed a possible role of these miRNAs in regulation of proper S-phase progression and cell proliferation.
Machiavelli Versus Concave Utility Functions: Should Bads Be Spread Out Or Concentrated?

Is wellbeing higher if the same number of negative events is spread out rather than bunched in time? Should positive events be spread out or bunched? We answer these questions exploiting quarterly data on six positive and twelve negative life events in the Household, Income and Labour Dynamics in Australia panel. Accounting for selection, anticipation, and adaptation, we find a tipping point when it comes to negative events: once people experience about two negative events, their wellbeing depreciates disproportionally as more and more events occur in a given period. For positive events, effects are weakly decreasing in size. So for a person's wellbeing both the good and the bad should be spread out rather than bunched in time, corresponding to the classic economic presumption of concave utility rather than Machiavelli's prescript of inflicting all injuries at once. Yet, differences are small, with complete smoothing of all negative events over all people and periods calculated to yield no more than a 12% reduction in the total negative wellbeing impact of negative events.
Rancang Bangun Sistem Keamanan Aliran Listrik Arus AC dengan Fingerprint menggunakan Arduino Nano

Semakin berkembangnya teknologi yang pesat saat ini, sangat berpengaruh terhadap meningkatnya produksi pada sebuah perusahaan elektronik untuk bisa memenuhi kebutuhan pasar, baik kebutuhan pasar elektronik rumah, kantor dan lain sebagainya yang sepanjang tahun terus meningkat bahkan tidak pernah sepi peminat. Dengan meningkatnya jumlah konsumen elektronik dari rumahan hingga tahap industri kecil hingga besar maka perlu adanya sistem kemanan pada arus yang mengalir pada rangkaian elektronik yang beredar dipasaran. Terlebih saat masih minimnnya produk elektronik dengan sistem keamanan yang lebih mengutamakan keamanan untuk menghindari konsleting pada arus elektronik. Oleh karena itu pada kesempatan penelitian ini dibuatlah sebuah sistem keamanan berbasis arduino nano pada aliran arus AC dengan menyematkan teknologi pembaca pola sidik jari atau yang biasa disebut dengan (fingerprint sensor), Sistem keamanan ini menggunakan metode pengumpulan data dari berbagai sumber jurnal,website, dan juga bengkel motor agar dapat diperolah hasil yang maksimal. Adapun hasil dari perancangan prototype sistem keamanan pada aliran arus AC ini belum terbilang sempurna dikarenakan masih banyak hal yang harus diteliti lebih lanjut dan diterapkan didalam modul arduino nano agar lebih banyak fitur yang bisa digunakan kedepannya.
Student Performance Prediction with Short-Term Sequential Campus Behaviors

As students’ behaviors are important factors that can reflect their learning styles and living habits on campus, extracting useful features of them plays a helpful role in understanding the students’ learning process, which is an important step towards personalized education. Recently, the task of predicting students’ performance from their campus behaviors has aroused the researchers’ attention. However, existing studies mainly focus on extracting statistical features manually from the pre-stored data, resulting in hysteresis in predicting students’ achievement and finding out their problems. Furthermore, due to the limited representation capability of these manually extracted features, they can only understand the students’ behaviors shallowly. To make the prediction process timely and automatically, we treat the performance prediction task as a short-term sequence prediction problem, and propose a two-stage classification framework, i.e., Sequence-based Performance Classifier (SPC), which consists of a sequence encoder and a classic data mining classifier. More specifically, to deeply discover the sequential features from students’ campus behaviors, we first introduce an attention-based Hybrid Recurrent Neural Network (HRNN) to encode their recent behaviors by giving a higher weight to the ones that are related to the students’ last action. Then, to conduct student performance prediction, we further involve these learned features to the classic Support Vector Machine (SVM) algorithm and finally achieve our SPC model. We conduct extensive experiments in the real-world student card dataset. The experimental results demonstrate the superiority of our proposed method in terms of Accuracy and Recall.
Short communication: Effects of the various source areas of Indonesian bay leaves (Syzygium polyanthum) on chemical content and antidiabetic activity

Abstract. Dewijanti ID, Mangunwardoyo W, Dwiranti A, Hanafi M, Artanti N. 2020. Short communication: Effects of the various source areas of Indonesian bay leaves (Syzygium polyanthum) on chemical content and antidiabetic activity. Biodiversitas 21: 1190-1195. Bay leaves (Syzygium polyanthum (Wight) Walp) are from an Indonesian plant species belonging to the Myrtaceae family. The Indonesian name for this plant is salam; it is found in Sumatra, Kalimantan, and the Java Islands. Its leaves are the part of the plant commonly used. Salam leaves are usually consumed by people as a food flavoring, but are also used as a traditional antidiabetic medicine. The purpose of this study was to discover the effects of salam leaves’ origins on their chemical content and antidiabetic activity. For this reason, salam leaf samples were collected from three different provinces in Java (West Java, Central Java, and East Java). The samples were extracted by boiling in water. Phytochemical screening, chemical analysis using TLC, HPLC, LC-MSMS, and FTIR, and antidiabetic in vitro testing using alpha-glucosidase inhibition methods were conducted on the salam leaves’ water extracts. The results showed that salam leaf extracts from all three provinces contained quercetin. However, the salam originating from East Java also contained coniferin, the salam from Central Java contained juncusol, and the salam from West Java contained retucine. The salam leaves originating from East Java showed the lowest antidiabetic activity, whereas salam leaf extract showed significantly higher antidiabetic activity. As conclusion, a plant’s growth origin affects its chemical content and antidiabetic activity.
A Study of Generalization of Stochastic Mirror Descent Algorithms on Overparameterized Nonlinear Models

We study the convergence, the implicit regularization and the generalization of stochastic mirror descent (SMD) algorithms in overparameterized nonlinear models, where the number of model parameters exceeds the number of training data points. Due to overpa-rameterization, the training loss has infinitely many global minima where they define a manifold of interpolating solutions. To have an understanding of the generalization performance of SMD algorithms, it is important to characterize which global minima the SMD algorithms converge to. In this work, we first theoretically show that in the overparameterized nonlinear setting, if the initialization is close enough to the manifold of global minima, which is usually the case in the high overparameterization setting, using sufficiently small step size, SMD converges to a global minimum. We further prove that this global minimum is approximately the closest one to the initialization in Bregman divergence, demonstrating the approximate implicit regularization of SMD. We then empirically confirm that these theoretical results are observed in practice. Finally, we provide an extensive study of the generalization of SMD algorithms. In our experiments, we show that on the CIFAR-10 dataset, SMD with ℓ10 norm potential (as a surrogate for ℓ∞) consistently general-izes better than SGD (corresponding to an ℓ2 norm potential), which in turn consistently outperforms SMD with ℓ1 norm potential.
Evaluation of Low Carbon Economy Development in China’s Provinces: Based on Entropy-OWA Algorithm and Grey Correlation Improvement TOPSIS

This study constructs the evaluation indicator system for low-carbon economic development level from the perspective of economic, energy consumption, low carbon, environmental, facilities and input status. Based on entropy-OWA operator weighting and grey correlation improvement TOPSIS comprehensive evaluation model, a comprehensive evaluation is made on the development level of low-carbon economy in 30 provinces and cities in China. The results show that the development level of China’s low-carbon economy is gradually decreasing from east to west in the regional distribution. The results show that the low carbon economy development level in China presents a gradual decline from east to west. The low-carbon economy in the eastern coastal areas is developing better, and lower in the western and northern regions. In order to promote the level of low-carbon economic development among different regions, the western and northern regions should focus on energy conservation and emission reduction while promoting economic development, and promote the development of low-carbon economy.
The complete mitochondrial genome of Punchinello butterfly, Zemeros flegyas (Lepidoptera: Riodinidae) and its phylogenetic implications

Abstract The complete mitochondrial genome (mitogenome) of Zemeros flegyas (Lepidoptera: Riodinidae) is 15,219 bp in length, harboring typical 37 mitochondrial genes (13 PCGs, 22 tRNAs, and 2 rRNAs) and an AT-rich region. The Z. flegyas mitogenome includes a cox1 gene with an atypical CGA(R) start codon and three genes (cox1, nad5, nad4) exhibiting incomplete stop codons. The putative AT-rich region is 385 bp long with several structures characteristic of lepidopteran. Phylogenetic analysis showed that Z. flegyas is closely related to other riodinids. The complete mitogenome data provided here would be useful for further understanding the higher systematics of Riodinidae.
DESIGN OF ADAPTIVE ARRAY WITH E-SHAPE SLOT RADIATOR FOR SMART ANTENNA SYSTEM

This paper presents the design of an 8-element linear array for Adaptive Antenna applications using the Least Mean Square (LMS) algorithm towards improving the directive gain, beam steering capabilities, half-power beam-width, side-lobe level, and bandwidth of array. A conventional patch antenna is optimized to operate at 3.6 GHz (5G applications) with two symmetrical slots and Quarter Wave Transformer for feeding, and this design is extended up to 8 elements using CST Microwave Studio parameterization. The Return Loss (S11), Directivity, HPBW, and VSWR of the antenna array are observed for the 2, 4, and 8 elements adaptive arrays. The inter-element spacing for resulting eight-element antenna array geometry is optimized to obtain maximum directive gain. This geometry appears promising in improving the directive gain from 7.6 dBi to 15.1 dBi for a single element to eight elements, respectively. Further, the LMS algorithm is used to compute the optimal complex weights, considering different angles for the desired User (+45◦ and −45◦) and Interferer (+20◦ and −20◦) during MATLAB simulation, and then these optimal weights are fed to antenna elements using CST for beam steering in a different direction. Maxima in the direction of user and nulls in the direction of interferer are obtained using CST software and found closely matching with MATLAB results.
Controlling the Perceived Sound Quality for Dialogue Enhancement With Deep Learning

Speech enhancement attenuates interfering sounds in speech signals but may introduce artifacts that perceivably deteriorate the output signal. We propose a method for controlling the trade-off between the attenuation of the interfering background signal and the loss of sound quality. A deep neural network estimates the attenuation of the separated background signal such that the sound quality, quantified using the Artifact-related Perceptual Score, meets an adjustable target. Subjective evaluations indicate that consistent sound quality is obtained across various input signals. Our experiments show that the proposed method is able to control the tradeoff with an accuracy that is adequate for real-world dialogue enhancement applications.
Liquid Water Path Steady States in Stratocumulus: Insights from Process-Level Emulation and Mixed-Layer Theory

Stratocumulus clouds constitute one of the largest negative climate forcings in the global radiation budget. This forcing is determined, inter alia, by the cloud liquid water path (LWP), which we analyze using a combination of Gaussian process emulation and mixed-layer theory. For nocturnal, nonprecipitating stratocumuli, we show that LWP steady states constitute an equilibrium primarily between radiative cooling and entrainment warming and drying. These steady states are approached from lower LWPs due to reduced entrainment, while higher LWPs are depleted by stronger entrainment. An analytical solution for the LWP steady state reveals not only the environmental conditions in which a stratocumulus cloud can be maintained, but also distinct analytical properties of the entrainment velocity that are required for a stable LWP steady state that opposes perturbations. In particular, the results highlight the importance of an entrainment velocity that increases strictly monotonically with the LWP if stratocumuli are to attain a stable LWP steady state. This is demonstrated through analysis of two commonly used mixed-layer entrainment parameterizations.
Determination of trypsin inhibitor activity of soy products: a collaborative analysis of an improved procedure

A more accurate and reproducible procedure is described for measurement of trypsin inhibitor activity of soybean products [e.g. soy flours, protein isolates and protein concentrates] than the method developed by Kakade [FSTA (1970) 2 4J369] for measuring antitryptic activity in raw soybeans. Because the modified procedure is particularly suitable in determining trypsin inhibitor activity of heat-processed samples, it is recommended for use in evaluating the heat destruction of trypsin inhibitors in soybean samples.
DEVELOPMENT OF A DIRECT METHOD OF ANALYZING TRANEXAMIC ACID LEVELS IN WHITENING CREAM USING REVERSED PHASE HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY

Objective: Whitening cream is a cosmetic that contains ingredients that can alleviate hyperpigmentation. Tranexamic acid (TA) is one of the potentialanti-pigmentation agents that work through inhibiting plasmin. TA is used in cosmetic formulations at a concentration of 2.5% as a whitening andmoisturizing agent. To date, research on TA in both cosmetics and other pharmaceutical products using high-performance liquid chromatography(HPLC) has not been done directly (without derivatization). Therefore, this study aimed to develop a simple and rapid analytical method for TA(without derivatization) in cosmetic cream samples using reverse-phase HPLC and water as a solvent.Methods: Optimization was conducted by evaluating several parameters that affect sample extraction, as well as composition and mobile phasetypes. The optimal method must fulfill suitability and validation requirements. The optimal method should be able to detect and quantify TA in creamsamples without derivatization.Results: The optimal analysis condition used a ultraviolet detector at a wavelength of 210 nm, acetonitrile: double-distilled water: phosphoric acid(64:34:2) as the mobile phase and a flow rate of 0.8 mL/min. The retention time of the analyte occurred in the 2nd min.Conclusion: The analytical method that met the validation requirements was characterized using parameters such as accuracy, precision, linearity,selectivity, limit, of detection, and limit of quantitation. This method is applicable for analyzing TA content in samples with a concentration of 1.02%.
Corporate Sustainability Practices and Supply Chain Management Performance of Bahraini Companies: An Initial Survey

Owing to the relatively small area and the decreasing natural resources of the Kingdom of Bahrain, businesses are searching for supply chains that are both sustainable and Greenly friendly. This study was conducted to determine the level of implementation of sustainable supply chain management (SSCM) practices and the effect of these SSCM activities on the efficiency of supply chain companies in Bahrain. Bahraini companies are adopting two classes of SSCM practices: Renewable Packaging and Green Procurement. Five key components that make up the overall SSCM performance of the respondent firms were identified: Operational Performance, Efficiency, Green Performance; Corporate Social Responsibility; and Socio-economic Performance. The use of recyclable materials as packaging and the option of using only items that are safe at their end-of-life have a direct, positive and more importantly, significant impact on operational efficiency. Sustainable SSCM practices of Bahraini firms have a positive and significant impact on their sustainable supply chain efficiency.