Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonal trend of climate variables in an area of the Caatinga phytogeographic domain

Wide variability in the rainfall regime and drought is characteristic of semi-arid regions. A better understanding of this variability can aid decision-making in the short, medium and long term. The aim of this study was to identify long-term patterns and trends in rainfall and temperature through the use of temporal patterns, in addition to assessing the duration of wet and dry periods. Daily historical series of rainfall and temperature for the district of Iguatu, Ceará were used. For rainfall, the annual and monthly climate normal (1974-2018) was calculated, in addition to the number of consecutive dry days (CDD) during the rainy season. The annual mean value for the maximum, mean, and minimum temperatures (1996-2017) was also calculated. Wide interannual variability in the rainfall was found, with very wet years (1985; 2009 and 2011) and very dry years (1979; 1983 and 1993) interspersed with periods of around average rainfall. When analysing the total occurrence of dry spells by class, it was found that events of from 5 to 10 days were the most frequent, and tended to reduce in number over the period under investigation. There was also an increase in the number of longer events, those over 16 days. Maximum annual temperatures show an increasing trend over the years, with minimum temperatures showing the smallest increases. It was concluded that extreme rainfall events are common, and alternate between rainy years and years of drought. The increase in maximum temperature and the reduction in rainfall express the extreme climate variability that may be a consequence of climate change.
Triassic igneous activities in the east flank of the East Kunlun orogenic belt: the Daheba complex example

ABSTRACT The Triassic igneous complexes in the east flank of the East Kunlun orogenic belt (E-KOB) provide a window through which to investigate the Mesozoic magmatism in the E-KOB. Here, we report the precise timing of Triassic magmatism and magma petrogenesis of different rock types in the east flank of the E-KOB based on the petrology, mineral chemistry, geochemistry, zircon geochronology and Lu-Hf isotopes. Zircon U-Pb dating reveals that the Daheba complex was crystallized in 242–239 Ma. The rocks display enrichment in large-ion lithophile elements (LILEs) and LREEs and depletion in high field strength elements (HFSEs) and HREEs, which are typical of subduction-related magmatic rocks. The fine-grained granites (FGs) are characterized by a high SiO2 content (72.25–74.28 wt. %), a high differentiation index (DI = 95) and marked depletion in Sr, Ba and Eu, which indicates that the FGs are highly fractionated I-type granitoids. The zircon εHf(t) values from −3.6 to −1.1 with two-stage model ages (TDM2) of 1496–1340 Ma, which suggests that they were derived from an ancient Mesoproterozoic lower crust. The similarity in the REE patterns of the mafic microgranular enclaves (MMEs) and host granites (HGs) indicates that the mixing between mafic and felsic magmas could have contributed to the chemical variation of the MMEs. The mafic melts were derived from the partial melting of the mantle that had been metasomatized by slab-derived fluids. The MMEs show typical igneous textures, acicular apatites, sieve texture of plagioclase and reverse zoning of plagioclase, which correspond to magma mixing during petrogenesis. Our geochemical and isotopic data suggest that the Daheba complex formed in an active continental margin setting closely related to the northward subduction of the Palaeo-Tethys Ocean Plate beneath the E-KOB. Graphical Abstract
Antihyperglycemic and Antihyperlipidemic Effect of Persea americana in High Fat Diet and Low Dose Streptozotocin Induced T2DM Male Albino Wistar Rats

Background: Type II diabetes is a major health problem worldwide, and is increasing in an alarming rate globally and in Ethiopia due to change in dietary habits and sedentary life style. Even though there is no effective cure for diabetes, early control of blood glucose significantly reduces the risk of diabetic complications. Different types of ingredients present in medicinal plants that act on a variety of targets by various modes and mechanisms are used to treat diabetes with minimum cost and side effect. Therefore, the objective of the present study was to investigate the antidiabetic effect of Persea americana mill fruit juice in high fat diet (HFD) and low dose Streptozotocin (STZ) induced type 2 diabetic (T2DM) male albino Wistar rats. Methods: Thirty six male albino Wistar rats weighing form 150-200g were divided in into six different groups: group I (normal control); Group II (diabetic control); Group III (metformin control) and Group IV – Group VI (treatment groups). Group I was fed on standard pellet and group II – group VI were fed on HFD for 4 weeks to induce pre-diabetes and insulin resistance followed by low dose STZ injection to induce T2DM. The treatment groups (group IV, V and VI) were given 632 mg/Kg, 1264 mg/Kg and 1896 mg/Kg/day of Persea americana fruit juice for six weeks, respectively to compare with normal, diabetic and 7mg/Kg metformin treated groups. After forty-five days of treatment, the rats were fasted overnight (12 to 14 hours), anaesthetized and blood sample was collected by cardiac puncture for biochemical tests (fasting blood glucose (FBG), lipid profile, total protein and creatinine). The results were analyzed using SPSS version 22.0. One way ANOVA followed by Post hoc Tukey’s multiple comparisons were done to compare the mean differences among the experimental groups, and p-values < 0.05 were considered statistically significant. Results: In high dose (1896 mg/Kg/day) Persea americana mill fruit juice treated group, food consumption, body weight, FBG, and LDL-C were significantly reduced and HDL-C was significantly increased (p < 0.005) compared with diabetic control group. Moderate dose (1264mg/Kg/day) treated group showed a decrease in FBG on 6th week and improve HDL-C levels. Treating the rats with Persea americana fruit juice changed TG, total protein and creatinine levels although not significant. Oral antidiabetes drug (metformin) significantly reduced pellet consumption, body weight, FBG and lipid profile.Conclusion: Overall, Persea americana mill fruit juice showed antihyperglycemic and antihyperlipidemic effect particularly through reduction of fasting blood glucose, LDL-C and increasing HDL-C in T2DM induced rats, thus it can be helpful in reducing the risk of diabetic complications.
SIW Cavity Backed Self-Diplexing Tunable Antenna

This communication presents a compact quarter-mode substrate integrated waveguide (QMSIW) cavity-backed self-diplexing tunable antenna. An open-ended slot is used to split the circular half-mode SIW (HMSIW) cavity resonator into two QMSIW cavity resonators. A varactor diode-loaded stub is added with each QMSIW resonator to achieve miniaturization and resonant frequency tuning. The miniaturization and tunability technique is demonstrated in a stand-alone QMSIW resonator and also in a QMSIW based self-diplexing antenna. The antenna is simulated, optimized, and subjected to practical testing inside a rectangular device. The device is treated as a quasi-receiver/transmitter, which consists of electronic circuitry and the proposed antenna. The resonant frequencies can be independently tuned by changing the values of the varactor diodes connected with each resonator. The simulated and measured results confirm that the proposed antenna can be tuned from 3.77 to 4.59 and from 4.96 to 6.1 GHz in the lower and higher frequency bands, respectively. The isolation between the two resonators in both bands is always better than 21 dB. The measured gains vary from 4.85 to 5.87 and 4.87 to 6.5 dBi in the lower and higher frequency bands, respectively. The proposed design shows stable and unidirectional radiation patterns in all tuning cases in both bands. The proposed self-diplexing tunable antenna is a competitive choice in compact and spectral-efficient radio frequency (RF) front ends where tuning is necessary for the efficient use of the frequency spectrum.
Prioritized Deployment of Dynamic Service Function Chains

Service Function Chaining and Network Function Virtualization are enabling technologies that provide dynamic network services with diverse QoS requirements. Regarding the limited infrastructure resources, service providers need to prioritize service requests and even reject some of low-priority requests to satisfy the requirements of high-priority services. In this paper, we study the problem of deployment and reconfiguration of a set of chains with different priorities with the objective of maximizing the service provider’s profit; wherein, we also consider management concerns including the ability to control the migration of virtual functions. We show the problem is more practical and comprehensive than the previous studies, and propose an MILP formulation of it along with two solving algorithms. The first algorithm is a fast polynomial-time heuristic that calculates an initial feasible solution to the problem. The second algorithm is an exact method that utilizes the initial feasible solution to achieve the optimal solution quickly. Using extensive simulations, we evaluate the algorithms and show the proposed heuristic can find a feasible solution in at least 83% of the simulation runs in less than 7 seconds, and the exact algorithm can achieve 25% more profit 8 times faster than the state-of-the-art MILP solving methods.
Multiple Selves and Multitasking: A Dynamic Longitudinal Study

This study integrates the theory of multiple selves within the theoretical framework of dynamic motivational activation (DMA) to identify the dynamic patterns of multiple self-concepts (i.e., the potential self, the actual self) in multitasking (e.g., primary and secondary activities) in daily life. A three-week experience sampling study was conducted on college students. Dynamic panel modeling results suggest that the self-concepts are both sustaining and shifting in daily activities and media activities. Specifically, the potential and actual selves sustained themselves over time in primary and secondary activities, but they also shifted from one to another to achieve a balance in primary activities over time. Interestingly, secondary activities were not driven by the alternative self-concept in primary activities, but instead, by the emotional experiences of primary activities. Furthermore, the findings identified that multitasking to fulfill their actual self did not motivate people to re-prioritize their potential self later.
Study the Wicking Phenomena of Cotton Woven Fabrics and its Constituent Yarns: Relation between Fabric Wicking and Yarn Wicking

ABSTRACT In this present paper, the wicking effect of cotton woven fabrics in different directions and wicking effect of its constituent yarns has been studied. Two different types of weaves have been examined to study the wicking performance. Increased fineness in yarns of ply and single structure shows lower wickability individually. However, when used in plain and twill weave samples, improvement of wicking occurs with an initial increase in yarn fineness, but further increase in fineness deteriorates the wickability of fabrics except the diagonal direction of twill design. The regression analysis has been done to show the relationship between fabric wicking and its constituent yarn wicking. Highly positive correlations between fabric and constituent yarns are observed in relation to wicking irrespective of fineness of yarns and direction of test. However, twill weave shows stronger relationship compared to plain weave.
Family learning: A process modeling method for cyber-additive manufacturing network

Abstract A Cyber-Additive Manufacturing Network (CAMNet) integrates connected additive manufacturing processes with advanced data analytics as computation services to support personalized product realization. However, highly personalized product designs (e.g., geometries) in CAMNet limit the sample size for each design, which may lead to unsatisfactory accuracy for computation services, e.g., a low prediction accuracy for quality modeling. Motivated by the modeling challenge, we proposed a data-driven model called family learning to jointly model similar-but-non-identical products as family members by quantifying the shared information among these products in the CAMNet. Specifically, the amount of shared information for each product is estimated by optimizing a similarity generation model based on design factors, which directly improve the prediction accuracy for the family learning model. The advantages of the proposed method are illustrated by both simulations and a real case study of the selective laser melting process. This family learning method can be broadly applied to data-driven modeling in a network with similar-but-non-identical connected systems.
Synthesis of BSA-Conjugated ZnO Nanoparticle for Pb2+ Sensing Applications

We report an ultra-low level of Lead ion (Pb2+) detection technique using solution-processed Bovine Serum Albumin (BSA) conjugated ZnO nanoparticle (BCZ) networks. Drop of the BCZ solution casting was performed in-between photolithography patterned two Au electrodes for sensor device. BCZ formation was confirmed by UV-Visible spectroscopy (UV-Vis spectroscopy) and Transmission Electron Microscopy (TEM) prior to device fabrication. The working principle of the sensor device depends on the variation of conductance with Pb2+ concentration. The limit of detection (LOD) of this fabricated device was determined as 0.1 pM (S/N > 3).
The impacts of simulated microgravity on the cell viability and Claudin-1 and Claudin-3 expression of MCF-7 breast cancer cells

It has been believed that microgravity directly can alter the structure, morphology, and function of biosystems and numerous research have been performed to recognize these alterations. Claudin proteins are the tight junctions’ main components. Additionally, they are crucial for the protection of the differentiated state of epithelial cells as well as for cell-cell interaction. This study aimed to explore the probable correlation between the claudin-1 and claudin-3 expression and microgravity condition. Additionally, examined the impacts of microgravity condition on cell morphology and viability. The gene expression in MCF-7 cells were assessed by real-time quantitative RT PCR. Afterward, the morphology and cellular viability of the cells were evaluated by an inverted microscope, MTT assay, and flow cytometry analysis. After 72 h of simulated microgravity, the claudin-1 and claudin-3 expression increased significantly (p <0.05). Also, MCF-7 cells after 72 h exposure to microgravity simulation comprised rounded cells, which were grouped and linked to each other making multicellular spheroids. However, microgravity simulation after 24 or 72 h did not have a remarkable effect on the viability of cells. The consequence of this research lied in the fact that simulated microgravity could not be a direct cure for breast cancer treatment. However, microgravity research can offer a unique in vitro tool to explore biomechanical effects in the biology of cancer. The findings obtained from this investigation can open fascinating research lines in astrobiology, biophysics, and cancer biology and can be utilized to improve survivability and life quality for malignancy patients.
THE EFFECT OF LIQUIDITY, COMPANY SIZE, AND INDEPENDENT COMMISSIONER ON TAX AGGRESSIVENESS

Submitted: 12 November 2020 Revised: 14 November 2021 Accepted: 3 Desember 2021 Each country has income to finance all government activities used to build infrastructure and public facilities for the community. One of them is sourced from tax revenue. Taxes are the main source of income for the state, one of which is the tax receipts that are deposited by business actors or companies. For the government, if the greater the tax paid by the company, the greater the state's revenue from the tax sector. However, it is of different interest for the company because taxes become a burden that can reduce the income the company receives each year. Of course this is contrary to the company's goal of earning as much income as possible and incurring minimal costs. The purpose of this study was to determine the effect of liquidity, company size, and independent commissioners on tax aggressiveness. This research was conducted at food and beverage subsector consumer goods companies listed on the IDX in the 2014-2018 period. The data analysis technique used is multiple linear regression. Based on the research results, it is known that partially liquidity has no significant effect on tax aggressiveness, firm size has a significant effect on tax aggressiveness, and independent commissioners do not have a significant effect on tax aggressiveness.
Updating Long-Held Assumptions About Fat Stigma: For Women, Body Shape Plays a Critical Role

Heavier bodies—particularly female bodies—are stigmatized. Such fat stigma is pervasive, painful to experience, and may even facilitate weight gain, thereby perpetuating the weight-stigma cycle. Leveraging research on functionally distinct forms of fat (deposited on different parts of the body), we propose that body shape plays an important but largely underappreciated role in fat stigma, above and beyond fat amount. Across three samples varying in participant ethnicity (White and Black Americans) and nation (United States, India), patterns of fat stigma reveal that, as hypothesized, participants differently stigmatized equally overweight or equally obese female targets as a function of target shape, sometimes even more strongly stigmatizing targets with less rather than more body mass. Such findings suggest value in updating our understanding of fat stigma to include body shape and in querying a predominating, but often implicit, theoretical assumption that people simply view all fat as ‘bad’ (and more fat as ‘worse’).
Weeds Detection and Classi�cation using Convolutional Long-Short-Term Memory

The smart agricultural robotic system can decrease the dependence on various traditional agriculture crop spraying methods such as pesticides, herbicides, and fertilizer. To meet the world population food requirements, conventional schemes are not sufficient for spraying agrochemicals to control the weeds and increase crop production. Therefore, a smart and intelligent farming system is introduced to increase the production of crops and to reach crop production target. In this paper, Deep Learning (DL) based algorithms is applied for the identification and classification of weed plants using combination of Convolutional Neural Networks (CNN) and Long-Short-Term Memory (LSTM). Convolutional Neural Networks (CNN) has a unique structure to get discriminative features for the input images, and LSTM allows to jointly optimize the classification. To validate the proposed scheme, nine kinds of weeds are classified using the proposed method such as vine weeds, three-leaf weeds, spiky weeds, and invasive creeping weeds. We carried out several extensive experiments and 99.36% of average classification accuracy is achieved. The obtained results show that the combination of CCN-LSTM has significantly higher classification capabilities in comparison to other existing prominent approaches.
Effect of Nanofiller Geometry on Network Formation in Polymeric Nanocomposites: Comparison of Rheological and Electrical Properties of Multiwalled Carbon Nanotube and Graphene Nanoribbon

The present work reveals results on the network formation of graphene nanoribbon (GNR) synthesized using a nonoxidative technique from multiwalled carbon nanotube (MWCNT). MWCNT and GNR presented comparable powder conductivity and dispersion state in a poly(vinylidene fluoride) (PVDF) matrix. This enabled us to purely discern the effect of geometrical features of the nanofillers on network formation by comparing the rheological and electrical percolation in the PVDF matrix. Unique features of the rheological response of PVDF/GNR nanocomposites, such as abrupt transition to a solid state, were interpreted according to a network structure activated by the formation of primary and secondary entanglements between adsorbed and bulk polymer chains. However, MWCNT nanocomposites presented a rheological behavior consistent with a strongly flocculated network structure formed through the direct tube–tube contacts and mechanical entanglements. Poor broadband electrical conductivity of the GNR nanocomposites compare.
Does gender diversity in supervisory boards affect gender diversity in management boards in Germany? An empirical analysis

Social aspects like gender diversity in the boardroom are becoming increasingly relevant and are a popular topic of public debate in the context of gender equality in business. However, there is little clarity about the potential spill-over effects of gender diversity. Both theory and empirical results have led to ambiguous conclusions with respect to the effect of gender diversity in the supervisory board on gender diversity in the management board. In addition, it is not clear whether the German gender quota legislation positively affects this relationship. This study analyses whether gender diversity in the supervisory board supports the gender diversity of the management board, and whether this relationship is affected by the gender quota legislation, focusing on the unique case of Germany. To cope with endogeneity concerns, this study employs a cross-lagged panel model with fixed effects using maximum likelihood structural equation modelling. The results of the analysis of the impact of the number of female supervisory board members on the number of female management board members do not support the view of positive spill-over effects of gender diversity in the environment of the German two-tier corporate governance system. Furthermore, this study finds no evidence of an effect of the German gender quota on this relationship. JEL Codes G38, M12, M14, M51
Fluidization of biomass: a correlation to assess the minimum fluidization velocity considering the influence of the sphericity factor

Abstract This paper deals with the influence of different definitions for evaluating the sphericity factor on the prediction of minimum fluidization velocity (U mf) of different agro-industrial/forestry biomass residues and sand. Three biowastes (sawdust, grape marc, and grape stalk) and sand were characterized by sieving, and sphericity was calculated using images obtained by scanning electron microscopy (SEM). Two particle size populations (with mean diameters and density corresponding to B and D Geldart groups) were adopted for each biomass. As for sand, particles with a mean diameter of 0.33 mm were used. Tests were carried out in a lab-scale fluidized bed. Bed pressure drop was measured as a function of the superficial velocity of air at two different initial bed heights, for each type of biomass and mixtures with sand. Ratios of 0.50 and 0.75 (v/v) were used for mixtures. For all cases, U mf values were calculated experimentally and were compared against predicted values obtained from Ergun's equation and other correlations. It was found that the methodology adopted for determining sphericity significantly influences the obtained value of U mf. The lowest relative error between predicted and experimental U mf values was obtained using Riley’s sphericity method. Finally, a new correlation for U mf was proposed.