Miracle-dz/UniFAR-FTUs huggingface dataset:
Interaction between phosphorus fertilizer and arbuscular mycorrhizal fungal inoculants on yield components of cassava in northern Guinea savanna alfisols of Nigeria

Field experiment was carried out in the Northern Guinea Savanna agro-ecology of Nigeria to examine the interaction between Phosphorus (P) fertilizer and Arbuscular Mycorrhizal Fungal (AMF) inoculants on cassava yield components. The experiment was laid in a split plot design with P fertilizers as main plot and AMF inoculants as subplots. There were three rates of P (0, 17.5, and 35 kg P 2 O 5 ha -1 ) and three levels of AMF inoculants (Control, Glomygel and Mycodrip). The result showed a significant interaction between P and AMF in root/shoot ratio and mycorrhizal response ratio. Highest root/shoot was recorded with combination of 17.5 P 2 O 5 ha -1 + control which depict increased sink strength. However, at 0 kg P 2 O 5 ha -1 , Glomygel and Mycodrip were 65.5% and 21.5% respectively greater than control. Mycorrhizal response was also shown to be highest with application of 0 kg P 2 O 5 ha -1 + Glomygel showing much influence of the inoculants where no P was applied. Single effects of P and AMF showed that dry yield components were significantly (p<0.01) increased. The root dry weight was increased by 3.21 and 5.16 t ha -1 as a result of application of 17.5 kg P 2 O 5 ha -1 and 35 kg P 2 O 5 ha -1 respectively over application of 0 kg P 2 O 5 ha -1 . Glomygel and Mycodrip inoculants recorded 28% and 4% total plant dry yield increment respectively over control. This study shows that both P and AMF increased dry yield of cassava in Northern Guinea Savanna of Nigeria. The reproducibility at scale and in time is required for proper recommendation. Keywords: AMF inoculants, Cassava, Alfisol, Mycorrhizal response, P fertilizers.
Simulation and Optimisation of Integrated Anaerobic-Aerobic Bioreactor (IAAB) for the Treatment of Palm Oil Mill Effluent

This study highlights an innovative piece of hybrid technology, whereby the combination of anaerobic and aerobic processes into a single reactor, namely, the integrated anaerobic–aerobic bioreactor (IAAB) can surpass the limits of conventional methods treating palm oil mill effluent (POME). Optimisation of IAAB using SuperPro Designer V9 simulator for maximum biogas yield while addressing its economic and environmental trade-offs was conducted for the first time. Parameters such as hydraulic retention time (HRT) and organic loading rate (OLR) were optimised in the anaerobic compartment from 10 days and 6.2 g COD/L day to 9 days and 6.9 g COD/L day, respectively. Furthermore, sludge recycle ratio was optimised from 20% to 50% in the aerobic compartment. The optimisation was successful where the biogas yield increased from 0.24 to 0.29 L CH4/g CODremoved with excellent Chemical Oxygen Demand (COD), and Biological Oxygen Demand (BOD) removal efficiencies up to 99% with 5.8% lower net expenditure. This simulation results were comparable against the pre-commercialized IAAB with 11.4% increase in methane yield after optimisation. Economic analysis had proven the optimised process to be feasible, resulting in return on investment (ROI), payback time, and internal rate of return (IRR) of 24.5%, 4.1 years, and 17.9%, respectively.
The ICON Single-Column Mode

The single-column mode (SCM) of the ICON (ICOsahedral Nonhydrostatic) modeling framework is presented. The primary purpose of the ICON SCM is to use it as a tool for research, model evaluation and development. Thanks to the simplified geometry of the ICON SCM, various aspects of the ICON model, in particular the model physics, can be studied in a well-controlled environment. Additionally, the ICON SCM has a reduced computational cost and a low data storage demand. The ICON SCM can be utilized for idealized cases—several well-established cases are already included—or for semi-realistic cases based on analyses or model forecasts. As the case setup is defined by a single NetCDF file, new cases can be prepared easily by the modification of this file. We demonstrate the usage of the ICON SCM for different idealized cases such as shallow convection, stratocumulus clouds, and radiative transfer. Additionally, the ICON SCM is tested for a semi-realistic case together with an equivalent three-dimensional setup and the large eddy simulation mode of ICON. Such consistent comparisons across the hierarchy of ICON configurations are very helpful for model development. The ICON SCM will be implemented into the operational ICON model and will serve as an additional tool for advancing the development of the ICON model.
A Review on the New Normal, Employee Wellbeing and the Role of HRM: A Tale of HR among the New Normal for the Employee Wellbeing

The sudden change in scenarios due to the COVID-19 pandemic has not only affected people’s financial situations but also their health and wellbeing. Psychological, physical discomfort along with on and off work schedules have led to stress for both the employer and employee. Gearing pressure of competition to survive in the dying economy has led to a path for the ‘New Normal’ where the current situation has been accepted as Normal with new adaptations. Employees, risking their lives and leaving the so-called comfort of their homes have had to step out to join the office while others have turned their homes into offices so as to work from home. They are at high risk of infection and stressed with the changed working scenario. The most challenging phase for the employers is the well-being of their employees for the continuous and timely work progress. The Role of HR has become the most crucial factor during this pandemic. Dealing with the employees and getting the work done with the limited resources in the crisis is the most challenging task. The present paper studies the three terms- 'New Normal', 'Employee Wellbeing' and 'Role of HR' within linked perspective and provides insight based on the various researches done in this field. It has been found that employee well-being is a well-talked topic and it has been a great concern for all the HR executives for a long time. Well- being of the employee ensures mutual gain for the employee and the organization both.
Management Earnings Forecasts Bias, Internal Control, and Stock Price Crash Risk: New Evidence from China

ABSTRACT Using a sample of Chinese listed firms over 2012–2018, we find robust evidence that management earnings forecasts bias is positively associated with crash risk, and this effect mainly exists in optimistic bias. Furthermore, higher levels of internal control can reduce management earnings forecasts bias and then reduce crash risk. Specifically, among the five components of internal control, risk assessment and communication are the main channels. In addition, the effect of internal control in weakening management earnings forecasts bias on stock price crash risk is more pronounced in firms with mandatory disclosure, timely disclosure and bad news. Our research shows that internal control plays an important role in mitigating stock price crash risk caused by management earnings forecasts bias.
Review—Power Sources for the Internet of Things

Wireless sensor networks have become integral to enabling numerous applications for the Internet of Things, such as environmental sensing or healthcare monitoring. Powering these networks has been the focus of signiﬁcant research efforts due to the need for reliable and continuous operation of the sensing nodes. In this review, we outline the progress made in the sensing nodes with a particular focus on their power demands. These requirements are used as a framework for surveying the theoretical limits and developments for various power sources, including energy storage, power distribution, and power scavenging techniques. Finally, we conclude by identifying that harvesting techniques are largely insufﬁcient for powering IoT nodes due to limited power densities or inconsistencies as to when power is harvested; accordingly, direct wiring and storage sources such as batteries are the most promising approaches for IoT applications.
STT-MRAM-Based Reliable Weak PUF

In recent years, micro-nano device characteristics like ferroelectrics and resistive switching are being used to build important security primitives such as Physical Unclonable Function (PUF). The micro-nano device-based hardware security primitives, although with higher security, energy efficiency, and integration density, suffer from serious reliability issues caused by process scaling. To mitigate this issue, this paper introduces a reconfigurable weak PUF based on spin-transfer torque magnetoresistive random-access memory (STT-MRAM), which adopts the crossing switches implemented with simple demultiplexes (DEMUXs) to improve the flexibility and reliability. Moreover, two algorithms, <monospace>neighboring bit lines</monospace> and <monospace>top-<inline-formula><tex-math notation="LaTeX">$n$</tex-math><alternatives><mml:math><mml:mi>n</mml:mi></mml:math><inline-graphic xlink:href="hu-ieq1-3095657.gif"/></alternatives></inline-formula></monospace>, are proposed to enlarge the gap between two parallel reading currents, thus further enhancing the reliability of PUF responses. Experimental results demonstrate that the proposed PUF scheme achieves good uniqueness (50.64 percent), uniformity (50.02 percent), and bit-aliasing (<inline-formula><tex-math notation="LaTeX">$\approx$</tex-math><alternatives><mml:math><mml:mo>≈</mml:mo></mml:math><inline-graphic xlink:href="hu-ieq2-3095657.gif"/></alternatives></inline-formula>49.80%). Particularly, the proposed method significantly improves the PUF reliability, achieving low bit error rate (BER <inline-formula><tex-math notation="LaTeX">$\leq$</tex-math><alternatives><mml:math><mml:mo>≤</mml:mo></mml:math><inline-graphic xlink:href="hu-ieq3-3095657.gif"/></alternatives></inline-formula> 2.13%) within the range of -20<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>∘</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="hu-ieq4-3095657.gif"/></alternatives></inline-formula>C to 90<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>∘</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="hu-ieq5-3095657.gif"/></alternatives></inline-formula>C.
Uses of radio emission spectroscopy for non-contact and in situ diagnostics of low pressure radio frequency plasma processing

We demonstrate that a passive non-contact diagnostic technique, radio emission spectroscopy (RES), provides a sensitive monitor of currents in a low pressure radio frequency (RF) plasma. A near field magnetic loop antenna was used to capture RF emissions from the plasma without perturbing it. The analysis was implemented for a capacitively coupled RF plasma with an RF supply at a frequency of 13.56 MHz. Real-time measurements are captured in scenarios relevant to contemporary challenges faced during semiconductor fabrication (e.g. window coating and wall disturbance). Exploration of the technique for key equipment parameters including applied RF power, chamber pressure, RF bias frequencies and chamber wall cleanliness shows sensitive and repeatable function. In particular, the induced RES signal was found to vary sensitively to pressure changes and we were able to detect pressure and power variations as low as ~2.5 %/mtorr and ~3.5 %/watt, respectively, during the plasma processing during a trial generic plasma process. Finally, we explored the ability of RES to monitor the operation of a multiple frequency low-pressure RF plasma system (f1 = 2 MHz, f2 = 162 MHz) and intermixing products which suggests strongly that the plasma sheaths are the primary source of this non-linear diode mixing effect.
Chemical Composition of Gas and Particle Phase Products of Toluene Photooxidation Reaction under High OH Exposure Condition

In the current study, the photooxidation reaction of toluene (C7H8) was investigated in a Potential Aerosol Mass Oxidation Flow Reactor (PAM OFR). The hydroxyl radical (OH) exposure of toluene in the PAM OFR ranged from 0.4 to 1.4 × 1012 molec cm−3 s, which is equivalent to 3 to 12 days of atmospheric oxidation. A proton transfer reaction-mass spectrometer (PTR-MS) and a scanning mobility particle sizer (SMPS) were used to study the gas-phase products formed and particle number changes of the oxidation reaction in PAM OFR. The secondary organic aerosol (SOA) formed in the PAM OFR was also collected for off-line chemical analysis. Key gas-phase reaction products of toluene, including glyoxal, methyl glyoxal, unsaturated carbonyl compounds, and benzaldehyde, were identified by the PTR-MS. Second generation products, including acetic acid, formaldehyde, formic acid, and acetaldehyde, were also detected. By comparing the mass spectrums obtained under different OH exposures and relative humidity (RH), changes in the two parameters have minimal effects on the composition of gas-phase products formed, expect for the spectrum obtained at OH exposure of 0.4 × 1012 cm−3 s and RH = 17%, which is slightly different from other spectrums. SMPS results showed that particle mass concentration increases with increasing OH exposure, while particle number concentration first increases and then decreases with increasing OH exposure. This result probably suggests the formation of oligomers at high OH exposure conditions. Off-line chemical analysis of the SOA sample was dominated by C4 diacids, including malic acid, citramalic acid, and tartaric acid. The well-known toluene SOA marker 2,3-Dihydroxy-4-oxopentanoic acid, as well as 2,3-dihydroxyglutaric acid, which has not been identified in previous toluene photooxidation experiments, were also detected in the SOA sample. Our results showed good agreements with the results of previous smog chamber studies of toluene photooxidation reaction, and they suggested that using PAM OFR for studies of oxidation reaction of different VOCs can be atmospherically relevant.
Monitoring the Impact of COVID-19 Lockdown on the Production of Nitrogen Dioxide (NO2) Pollutants Using Satellite Imagery: A Case Study of South Asia

Among the numerous anthropogenic pollutants, nitrogen dioxide (NO2) is one of the leading contaminants mainly released by burning fossil fuels in industrial and transport sectors. This study evaluates the impact of COVID-19 lockdown on the growing trend of NO2 emissions in South Asia. Satellite imagery data of Sentinel-5 Precursor with Tropomi instrument was employed in this study. The analysis was performed using time series data from February–May 2019 and February–May 2020. The time frame from February–May 2020 was further divided into two sub-time-frames, i.e., from 1 February–20 March (pre-lockdown) and from 21 March–May 2020 (lockdown). Results show the concentration of NO2 pollutants over the region declined by 6.41% from February–May 2019 to February–May 2020. Interestingly, an increasing trend of NO2 concentration by 6.58% occurred during the pre-lockdown phase in 2020 (1 February–20 March) compared to 2019 (February–May). However, the concentration of NO2 pollutants reduced considerably by 21.10% during the lockdown phase (21 March–10 May) compared to the pre-lockdown phase in 2020. Furthermore, the country-specific detailed analysis demonstrates the significant impact of COVID-19-attributed lockdown on NO2 concentration in South Asia.
Confidence-Based 6D Object Pose Estimation

The aim of this paper is to estimate the six-degree-of-freedom (6-DOF) poses of objects from a single RGB image in which the target objects are partially occluded. Most recent studies have formulated methods for predicting the projected 2-D locations of 3-D keypoints through a deep neural network and then used a PnP algorithm to compute the 6-DOF poses. Several researchers have pointed out the uncertainty of the predicted locations and modelled it according to predefined rules or functions, but the performance of such approaches may still be degraded if occlusion is present. To address this problem, we formulated 2-D keypoint locations as probabilistic distributions in our novel loss function and developed a confidence-based pose estimation network. This network not only predicts the 2-D keypoint locations from each visible patch of a target object but also provides the corresponding confidence values in an unsupervised fashion. Through the proper fusion of the most reliable local predictions, the proposed method can improve the accuracy of pose estimation when target objects are partially occluded. Experiments demonstrated that our method outperforms state-of-the-art methods on a main occlusion data set used for estimating 6-D object poses. Moreover, this framework is efficient and feasible for realtime multimedia applications.
Genetic Dissection of Phosphorous Uptake and Utilization Efficiency Traits Using GWAS in Mungbean

Mungbean (Vignaradiata L. Wilczek) is an early maturing legume grown predominantly in Asia for its protein-rich seeds. P deficiency can lead to several physiological disorders which ultimately result in a low grain yield in mungbean. The genetic dissection of PUpE (Puptake efficiency) and PUtE (P utilization efficiency) traits are essential for breeding mungbean varieties with a high P uptake and utilization efficiency. The study involves an association mapping panel consisting of 120 mungbean genotypes which were phenotyped for total dry weight, P concentration, total P uptake, and P utilization efficiency under low P (LP) and normal P (NP) conditions in a hydroponic system. A genotyping-by-sequencing (GBS) based genome-wide association study (GWAS) approach was employed to dissect the complexity of PUpE and PUtE traits at the genetic level in mungbean. This has identified 116 SNPs in 61 protein-coding genes and of these, 16 have been found to enhance phosphorous uptake and utilization efficiency in mungbeans. We identified six genes with a high expression (VRADI01G04370, VRADI05G20860, VRADI06G12490, VRADI08G20910, VRADI08G00070 and VRADI09G09030) in root, shoot apical meristem and leaf, indicating their role in the regulation of P uptake and utilization efficiency in mungbean. The SNPs present in three genes have also been validated using a Sanger sequencing approach.
Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2)

Earth system models are intended to make long‐term projections, but they can be evaluated at interannual and seasonal time scales. Although the Community Earth System Model (CESM2) showed improvements in a number of terrestrial carbon cycle benchmarks, relative to its predecessor, our analysis suggests that the interannual variability (IAV) in net terrestrial carbon fluxes did not show similar improvements. The model simulated low IAV of net ecosystem production (NEP), resulting in a weaker than observed sensitivity of the carbon cycle to climate variability. Low IAV in net fluxes likely resulted from low variability in gross primary productivity (GPP)—especially in the tropics—and a high covariation between GPP and ecosystem respiration. Although lower than observed, the IAV of NEP had significant climate sensitivities, with positive NEP anomalies associated with warmer and drier conditions in high latitudes, and with wetter and cooler conditions in mid and low latitudes. We identified two dominant modes of seasonal variability in carbon cycle flux anomalies in our fully coupled CESM2 simulations that are characterized by seasonal amplification and redistribution of ecosystem fluxes. Seasonal amplification of net and gross carbon fluxes showed climate sensitivities mirroring those of annual fluxes. Seasonal redistribution of carbon fluxes is initiated by springtime temperature anomalies, but subsequently negative feedbacks in soil moisture during the summer and fall result in net annual carbon losses from land. These modes of variability are also seen in satellite proxies of GPP, suggesting that CESM2 appropriately represents regional sensitivities of photosynthesis to climate variability on seasonal time scales.
Assessing the Impact of Membrane Deformations on Wing Sail Performance

The aim of this research is to quantify the membrane deformations and their impact on performance for a ribbed wing sail. A 1m x 0.8m rectangular planform NACA0012 foil was designed to replicate a single section of a wing-sail. Two foils were manufactured based on this geometry, one out of solid foam and one using a rib and membrane structure. These were tested in the R.J. Mitchell closed return 3.6 m x 2.5 m wind tunnel at the University of Southampton. Their aerodynamic performance was assessed over a range of angles of attack using a six-component force balance showing the overall performance of the membrane wing was reduced by between 5-11% depending on the analysis conducted. A stereo camera system was used to perform Digital Image Correlation (DIC) in order to quantify the full field deformation of the membrane wing structure whilst under aerodynamic load. This showed membrane deformations of up to 15% of the section thickness. The experimental membrane displacements were then used to create a deformed wing sail geometry, removing the effect of foil bend and twist, allowing a CFD investigation of the impact of membrane deformations alone. This indicated that the static membrane deformations resulted in a decrease in performance of up to 1.3% compared to the rigid aerofoil.
Monday-focused tailored rapid interactive mobile messaging for weight management 2 (MTRIMM2): results from a randomized controlled trial.

Background Text-messaging interventions can reach many individuals across a range of socioeconomic groups, at a low cost. Few randomized controlled trials (RCTs) of text-messaging weight loss interventions have been conducted in United States. Methods From September of 2016 to September of 2018, we conducted a two-parallel group, superiority, RCT of a 16-week text-messaging, weight loss intervention in Baltimore, Maryland, in overweight and obese adults younger than 71, who were able to receive text-messages. Our objective was to assess the effect of receiving the message content only (in printed documents distributed at baseline and week 8), versus receiving messages via short messaging service (SMS) on weight loss (primary outcome), body mass index, perceived exercise benefits and barriers, self-efficacy, and physical activity (PA). The random allocation sequence was equally balanced intervention groups by gender and age groups. Participants were randomized after the baseline assessment. Then, participants and most study staff were unblinded. Follow-up assessments were conducted at 8-, 16-, and 42-week post randomization. We performed intention-to-treat analysis using mixed linear regression models. Results Of the 155 adults randomized (printed messages =77, SMS =78), 87.1% were women, 53.5% were African Americans, and 93.5% non-Hispanic. Participants who completed at least one follow-up assessment were included in regression analyses (n=145, printed messages =74, SMS =71). Compared to baseline, at the 42-week assessment, the average percent weight loss was 1.23 for the SMS group (P=0.006) and 0.86 for the printed messages group (P=0.047). Both groups experienced small reductions in weight (printed messages: -0.96 kg, P=0.022; SMS: -1.19 kg, P=0.006), BMI (printed messages: -0.32, P=0.035; SMS: -0.52, P=0.002), and percent energy from fat consumption (printed messages: -1.43, P=0.021; SMS: -2.14, P≤0.001). No statistically significant between groups differences were detected for any of the study outcomes. SMS response rates were not statistically significantly associated with study outcomes. No adverse events were reported. Conclusions A semi-tailored SMS weight loss intervention among overweight and obese adults was not statistically superior in efficacy to paper-based messaging. Trial Registration ClinicalTrials.gov Identifier: NCT04506996.