Miracle-dz/UniFAR-FTUs huggingface dataset:
Source‐sum‐power minimization in multiple‐sensor single‐AF relay‐based IoT networks with outage constraints and under hardware impairments and imperfect CSI

This paper investigates the optimal power allocation to minimize the source‐sum‐power consumption of Internet of Things networks in the presence of transceiver hardware impairments and imperfect channel estimates, where N single‐antenna sensors communicate with a single‐antenna destination via a single‐antenna half‐duplex amplify‐and‐forward relay. We assume that the consideration of remote‐area wireless sensor application restricts the direct communication between the sensors and destination. Specifically, we first derive the exact and asymptotic outage probability expressions under hardware impairments and imperfect channel estimates over Rayleigh fading channels. Then, we formulate and evaluate an optimization problem for source‐sum‐power minimization taking both the power and outage constraints into account in the presence of transceiver hardware impairments and imperfect channel estimates with the help of Karush‐Kuhn‐Tucker conditions. The numerical results corroborate our theoretical findings and demonstrate the optimality of the considered system. Moreover, our results reveal that (i) the system's diversity order reduces to zero because of the irreducible error floor occurs from the fixed channel estimation errors, (ii) the source‐sum‐power consumption reduces with the increased maximum available relay power and increases as the number of sensor nodes increases, (iii) the hardware impairments and imperfect channel estimates significantly increase the source‐sum‐power consumption, and (iv) the proposed source‐sum power minimization scheme can optimize the performance of the considered system. Also, we compare our proposed optimal power allocation scheme with the uniform power allocation scheme, from which it is shown that the proposed scheme is better than the uniform one irrespective of the involved parameters. Furthermore, we compare our proposed scheme with some existing approaches, such as time division scheme and decode‐and‐forward relay scenario, in terms of outage probability and source‐sum‐power minimization.
Implicit Ambivalence: A Driving Force to Improve Relationship Problems

Implicit ambivalence involves holding strong positive and negative implicit evaluations toward the same object. This state is common in close relationships because even the most satisfying partnerships involve in conflicts and other frustrating experiences that can be explained away through effortful motivated reasoning yet remain in memory as mental representations involving the partner. In fact, it appears normative for implicit measures of partner attitudes to reveal implicit ambivalence. Despite being common, however, little is known about the consequences of implicit ambivalence. The present longitudinal investigation provides initial evidence that implicit ambivalence can motivate relationship improvements. Across two studies of newlywed couples (N = 448 individuals), multilevel dyadic modeling revealed that higher implicit ambivalence was associated with higher motivation to make efforts to improve current marital problems, which predicted reduced marital-problems severity reported by the partner and increased marital satisfaction reported by both spouses 4 months later.
Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Study

Quality is a very important parameter for all objects and their functionalities. In image-based object recognition, image quality is a prime criterion. For authentic image quality evaluation, ground truth is required. But in practice, it is very difficult to find the ground truth. Usually, image quality is being assessed by full reference metrics, like MSE (Mean Square Error) and PSNR (Peak Signal to Noise Ratio). In contrast to MSE and PSNR, recently, two more full reference metrics SSIM (Structured Similarity Indexing Method) and FSIM (Feature Similarity Indexing Method) are developed with a view to compare the structural and feature similarity measures between restored and original objects on the basis of perception. This paper is mainly stressed on comparing different image quality metrics to give a comprehensive view. Experimentation with these metrics using benchmark images is performed through denoising for different noise concentrations. All metrics have given consistent results. However, from representation perspective, SSIM and FSIM are normalized, but MSE and PSNR are not; and from semantic perspective, MSE and PSNR are giving only absolute error; on the other hand, SSIM and PSNR are giving perception and saliency-based error. So, SSIM and FSIM can be treated more understandable than the MSE and PSNR.
Antiferromagnetic ordering and excitonic pairing in AA-stacked bilayer graphene

In this paper, we describe the antiferromagnetic and excitonic correlations in the AA-stacked bilayer graphene. We consider the applied external electric field potential to the structure which leads to the electronic charge imbalance between the layers in the system. By using the generalized two-layer Hubbard Hamiltonian, we consider different particle-filling regimes in the layers. We calculate the important energy scales in the system and we establish the conditions for the appearance of the antiferromagnetic order in the system. We consider both large and small Coulomb interaction limits in the layers and the effect of the electric field potential on the calculated order parameters. We discuss the coexistence of antiferromagnetism and excitonic phases and we show that they can coexist only in the regime away from half-filling. In the case away from the half-filling, we show the existence of a critical value ${U}_{\mathrm{C}}$ of the Coulomb interaction potential at which we establish the transition from the single-valued to the triple-valued excitonic states, governed by the strong electronic reconfiguration, in the system. The zero-temperature limit is considered in the problem.
Investigations into early larval feeding practices for the Tiger Barb
 Puntigrus tetrazona

The Tiger Barb Puntigrus tetrazona is one of the highest trade volume freshwater species in the ornamental ﬁ sh industry. Culture of larval Tiger Barb is largely dependent on live feeds at ﬁ rst feeding and throughout early life stages, leading to increased cost relative to the use of commercially produced microparticulate diets (MDs). Potential for the successful culture of Tiger Barb by using MDs from ﬁ rst feeding was evaluated here, with a focus on the physiological characteristics that limit digestive capacity in larval cyprinids, as well as the hypothetical bene ﬁ t of including feed attractants in formulated larval feeds. Comparable growth and survival were achieved for the ﬁ rst 14 d of feeding with one of three MDs when compared to feeding with brine shrimp Artemia spp. Histological preparation revealed evidence for a fully functional pharyngeal jaw structure, including pharyngeal teeth and a pharyngeal pad, from 6 d posthatch, which coincided with ﬁ rst feeding. The masticatory function of these structures likely facilitated the break-down and subsequent utilization of the relatively complex macronutrients that are characteristic of MDs. Inclusion of top-coated potential attractants (tryptophan, taurine, trimethylglycine betaine, or a mix of the three) with the most successful MD from the original trial failed to induce an increased feeding response, as evidenced by the observation of similar feeding incidence, total larval protein content, and tryptic enzyme activity relative to a negative control MD without added attractants. The results of this research suggest that the successful culture of larval Tiger Barb is possible with the use of commercially available MDs, potentially leading to cost savings and increased resilience of producers in the ornamental aquaculture industry.
Gymnema sylvestre (Gurmar): A Potent Herb with Anti-diabetic and Antioxidant Potential

Introduction: Diabetes Mellitus is a metabolic disorder with high blood sugar level. Type 2 is the common form. The herbal remedies for diabetes treatment is an area of research with a huge potential for the progress in the growth of inexpensive alternative medicine with low or no side effects. In this paper, reviews mainly focused on traditionally used medicinal herb, Gymnema sylvestre and its bioactive components and their mode of actions. Method: Relevant information was collected from scientific journals, research papers, books and various medicinal reviews. Result: This review provides a comprehensive report on Gymnema sylvestre having antidiabetic and antioxidant activity due to its bioactive compounds like oleanines (Gymnemic acid, Gymnema saponins), dammarenes (Gymnemasides), anthraquinones, flavones, hentriacontane, pentatriacontane, phytin, resin, tartaric acid, formic acid, butyric acid, lupeol, β-amyrene related glycosides and anthraquinones, alkaloid like gymnamine, flavonoids, cinnamic acid, folic acid, ascorbic acid etc. Conclusion: Considering the presence of bioactive compounds present in Gymnema sylvestre, this review is aimed to summarize the information of the chemical constituents and their antidiabetic activities and specially to detect the relation between antioxidants and antidiabetic compounds regarding blood sugar reduction in diabetes.
Information encoding and transmission profiles of first-language (L1) and second-language (L2) speech*

Abstract Inspired by information theoretic analyses of L1 speech and language, this study proposes that L1 and L2 speech exhibit distinct information encoding and transmission profiles in the temporal domain. Both the number and average duration of acoustic syllables (i.e., intensity peaks in the temporal envelope) were automatically measured from L1 and L2 recordings of standard texts in English, French, and Spanish. Across languages, L2 acoustic syllables were greater in number (more acoustic syllables/text) and longer in duration (fewer acoustic syllables/second). While substantial syllable reduction (fewer acoustic than orthographic syllables) was evident in both L1 and L2 speech, L2 speech generally exhibited less syllable reduction, resulting in low information density (more syllables with less information/syllable). Low L2 information density compounded low L2 speech rate yielding very low L2 information transmission rate (i.e., less information/second). Overall, this cross-language comparison establishes low information transmission rate as a language-general, distinguishing feature of L2 speech.
Trials and Tribulations in the Frontline Treatment of Older Adults with Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a heterogeneous aggressive hematologic malignancy derived from malignant clones that promote their own growth and survival at the expense of normal hematopoiesis resulting in life-threatening bleeding and infections. Traditional initial AML therapy has been centered on a backbone of intensive chemotherapy often composed of an anthracycline and cytarabine. This strategy has proven most effective in patients less than 60 years of age due to both patient-related tolerability factors as well as changes in AML biology centered on chemotherapy refractory mutational profiles that are seen with advancing age. Recent improvements in frontline AML therapy have been seen in patients 60 years of age and over, a population most typically referred to as “older” adult AML. Herein, we describe the characteristics of “older” adult AML, review the differences in outcomes amongst those 60–75 and those over 75 years of age, and cite challenges in delivering frontline therapies within this group based not only on therapeutic toxicity but also on the patient’s overall level of “fitness” and inherent biology. We also discuss the role of targeted therapies that inhibit specific mutations and have the potential to deliver improved efficacy with less side effects while also recognizing that some selected older AML patients still benefit from intensive induction therapy.
Life lessons: Examining sources of racial and ethnic disparity in federal life without parole sentences*

Alongside capital punishment, sentences to life without the possibility of parole are one of the most distinctive aspects of the American system of criminal punishment. Unlike the death penalty, though, almost no empirical work has examined the decision to impose life imprisonment. The current study analyzes several years of recent federal sentencing data (FY2010–FY2017) to investigate underlying sources of racial disparity in life without parole sentences. The analysis reveals disparities in who receives life imprisonment, but it finds these differences are attributable mostly to indirect mechanisms built into the federal sentencing system, such as the mode of conviction, mandatory minimums, and guidelines departures. Both Black and Hispanic offenders are more likely to be eligible for life sentences under the federal guidelines, but conditional on being eligible, they are not more likely to receive life sentences. Findings are discussed in relation to ongoing debates over racial inequality and the growing role that life imprisonment plays in American exceptionalism in punishment.
Reflection coefficients of P‐waves in partially saturated fractured media

Wave‐induced fluid flow, an important mechanism in seismic wave attenuation, is considered in the amplitude variation with the offset technique. In a fractured marine carbonate reservoir, fractures and pores develop simultaneously, such that wave‐induced flow is an important mechanism in attenuation caused by the fluid flow between pores as well as between pores and fractures. However, these two types of attenuation are typically investigated separately or studies assume that the pores and fractures are dry or saturated by the same fluid. Rock pores are usually saturated by a mixture of two or more fluids, such that the fracture and pore filling fluids may be different. During variation with offset reservoir prediction and fluid identification, the influence that the porosity, fracture, and fluid have on the P‐wave reflection coefficient should be considered. The patchy saturation model can describe the seismic wave dissipation caused by the wave‐induced flow between pore fluids, whereas the Norris model can describe seismic wave dissipation caused by the fluid flow between fractures and pores. This study considers both the patchy saturation model and Norris model to calculate the amplitude variation with the offset P‐wave reflection coefficient under different conditions. Combining the saturation and Norris models forms a new model, which is regarded as a transversely isotropic medium with a vertical symmetric axis, and can be extended to any incident angle through the relaxation function and the high‐ and low‐frequency elastic limits of the stiffness tensor, where the complete effective stiffness tensor of the new model can be obtained. Finally, the amplitude variation with offset reservoir technology is used to determine the influence of model parameters on the reflection coefficient of P‐waves under different angles and frequencies, including fracture weakness, fluid saturation and pore fluid saturation.
An Ensemble 3D Convolutional Neural Network for Spatiotemporal Soil Temperature Forecasting

Soil temperature (ST) plays an important role in agriculture and other fields, and has a close relationship with plant growth and development. Therefore, accurate ST prediction methods are widely needed. Deep learning (DL) models have been widely applied for ST prediction. However, the traditional DL models may fail to capture the spatiotemporal relationship due to its complex dependency under different related hydrologic variables. Hence, the DL models with Ensemble Empirical Mode Decomposition (EEMD) are proposed in this study. The proposed models can capture more complex spatiotemporal relationship after decomposing the ST into different intrinsic mode functions. Therefore, the performance of models is further improved. The results show that the performance of DL models with EEMD are better than that of corresponding DL models without EEMD. Moreover, EEMD-Conv3d has the best performance among all the experimental models. It has the highest R2 ranging from 0.9826 to 0.9893, the lowest RMSE ranging from 1.3096 to 1.6497 and the lowest MAE ranging from 0.9656 to 1.2056 in predicting ST at the lead time from one to five days. In addition, the lines between predicted ST and observed ST are closer to the ideal line (y = x) than other DL models. The results show that our EEMD-Conv3D can better capture spatiotemporal correlation and is an applicable method for predicting spatiotemporal ST.
Comparative Analysis on Thermo-physiological Behavior of Eri Silk, Wool and Bamboo Knitted Fabrics Toward Sportswear

ABSTRACT Layered fabrics are utilized for the development of active sport wear applications due to their thermo-physiological properties. In this study, nine different types of knitted fabrics were developed using mill spun yarns of Eri silk, Wool (worsted), and Bamboo with three different knit structures such as single jersey, single pique, and honeycomb. The thermo-physiological properties such as thermal conductivity, thermal resistance, thermal absorptivity, air permeability, and water vapor permeability were studied. Further to this, the moisture management properties such as wetting time, absorption rate, spreading speed, and maximum wet radius of the knitted fabrics were measured. Finally, the overall thermal comfort fabric was compared both subjective and objective manner and found that Eri silk based knitted honeycomb structure was highest rated than other samples.
The Effect of Ammonia Toxicity on Methane Production of a Full-Scale Biogas Plant—An Estimation Method

Ammonia accumulation in biogas plants reactors is becoming more frequently encountered, resulting in reduced methane (CH4) production. Ammonia toxicity occurs when N-rich substrates represent a significant part of the biogas plant’s feedstock. The aim of this study was to develop an estimation method for the effect of ammonia toxicity on the CH4 production of biogas plants. Two periods where a biogas plant operated at 3200 mg·L−1 (1st period) and 4400 mg·L−1 (2nd period) of ammonium nitrogen (NH4+–N) were examined. Biomethane potentials (BMPs) of the individual substrates collected during these periods and of the mixture of substrates with the weight ratio used by the biogas plant under different ammonia levels (2000–5200 mg·L−1 NH4+–N) were determined. CH4 production calculated from the substrates’ BMPs and the quantities used of each substrate by the biogas plant was compared with actual CH4 production on-site. Biogas plant’s CH4 production was 9.9% lower in the 1st and 20.3% in the 2nd period in comparison with the BMP calculated CH4 production, of which 3% and 14% was due to ammonia toxicity, respectively. BMPs of the mixtures showed that the actual CH4 reduction rate of the biogas plant could be approximately estimated by the ammonia concentrations levels.
The Role of Ultra-Radical Surgery in the Management of Advanced Ovarian Cancer: State or Art

The ovarian cancer, also known as “silent killer”, has remained the most lethal gynaecological malignancy. The single independent risk factor linked with improved survival is maximum cytoreductive effort resulting in no macroscopic residual disease. This could be gained through ultra-radical surgery which demands tackling significant tumour burden in pelvis, lower and upper abdomen which usually constitutes bowel resection, liver mobilisation, ancillary cholecystectomy, extensive peritonectomy, diaphragmatic resection, splenectomy, resection of enlarged pelvic, paraaortic, and rarely cardio-phrenic lymph nodes in order to achieve optimal debulking. The above can be achieved through a holistic approach to patient’s care, meticulous patient selection, and full engagement of the family. The decision needs to be carefully balanced after obtaining an informed consent, and an appreciation of the impact of such surgery on the quality of life against the survival benefit. This chapter will describe the complexity and surgical challenges in the management of advanced ovarian cancer.
In situ measurements of lead and other trace elements in abyssal peridotite sulfides

Abstract In the mantle, base metal sulfides have been proposed as the main host for many chalcophile and siderophile elements. This includes elements such as Pb, Se, and Te, which are often used as tracers of processes ranging from planetary accretion to mantle melting. We present in situ measurements of these elements, along with As, Sb, Ag, Au, and Cl, in abyssal peridotite sulfides to provide constraints on the storage of these elements in the mantle. A total of 152 sulfides from 11 peridotites and 1 pyroxenite from the Gakkel and Southwest Indian ridges were analyzed. The sulfides are pentlandites, some of which contain either discrete chalcopyrite domains or Cu-rich intergrowths. Trace-element concentrations in 108 unaltered sulfides range from 2 to 36 ppm Pb, 45 to 250 ppm Se, <4 to 360 ppm Te, <1.5 to 1900 ppm As, 2 to 420 ppm Sb, 2 to 340 ppm Ag, 2 to 770 ppb Au, and 0.2 to 1000 ppm Cl. Tellurium abundances are highly variable within sulfides, which is likely due to the presence of telluride micro- or nano-phases. Based on morphology, composition, and the absence of monosulfide solid solution, the sulfides are interpreted to have formed by fractional crystallization from sulfide melt during conductive cooling of the mantle beneath the ridge axis. The average sulfide Pb concentration of 4 ppm can be reproduced by >90% fractional crystallization from a sulfide melt. The remaining sulfide melt, which is modeled to contain 800 ppm Pb, will dissolve into silicate melt as it rises through the mantle due to the increasing solubility of sulfur in silicate melt as pressure decreases. However, the amount of sulfide melt that remains after fractional crystallization is too low (mode of <0.005%) to contribute a significant amount of Pb to mid-ocean ridge basalts. We conclude that sulfides are not the main host for mantle Pb, even prior to the onset of any melting, and that the majority of mantle Pb is stored in silicate phases.
Modelling the dispersion of harmful algal bloom (HAB) in the Thermaikos Gulf (NW Aegean Sea)

Coastal hydrodynamics are directly related to important environmental and ecological issues. This paper focuses on the study of harmful phytoplankton cells’ dispersion, after an episode of an algal bloom, based on mathematical modeling. The case of Thermaikos Gulf was used for the simulation. The necessary hydrodynamic information was obtained by the application of a 2D hydrodynamic model directly coupled with a transport model for the simulation of the harmful cells’ dispersion. The model describes hydrodynamic and biological processes such as advection, dispersion and cell growth and losses. The mechanical processes are described with the mass and momentum conservation equations while the movement of the particles is described with the Random Walk simulation. The biological processes of cell growth rate were described as a function of temperature light and nutrients, and embodied to the simulation as input data for the model runs while the biological losses are simulated by the removal of particles randomly selected from the field. The reliability of the model was tested using data of a real algal bloom episode. Finally the study is completed with the detection of the distribution of the harmful phytoplankton cells in Thermaikos for different wind conditions and different sources of algal bloom.