Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemometrics Approach to QuEChERS-dSPE for Multi-Standard Determination of Pesticides in Blank Samples of Milli-Q-Water Using High-Performance Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)

The development of the best efficient technique for multi-pesticide determination in food samples is one of the best ways to address issues concerned with the use of pesticides in agricultural practices. Even though, several conventional techniques have been used earlier such as solid-phase extraction (SPE) and liquid phase microextraction (LPME), unfortunately, these treatment techniques possess poor sensitivity towards targeted analytes due to lack of modifications and optimization which provides an optimum condition for the analyses. In the present work however, chemometrics (multivariate) approach was used as response surface methodology (RSM) for optimising significant factors of quick, easy, cheap, effective, rugged and safe (QuEChERS) with the dispersive solid phase extraction (dSPE) technique. The Blanket-Burman (screening) and Box-Behnken (optimising) design generated by Minitab statistical software were used for the screening and optimisation of significant factors, respectively as well as quantification using total chromatographic peak areas (TCPA) responses of high-performance liquid chromatography-tandem mass spectrometry instrument. Eventually, the acquired average TCPA recovery (56%) for the RSM optimized QuEChERS-dSPE technique was favoured over that of default technique (44%) after comparative studies. This justifies the validity of the optimized method to play an important role in the determination of multi-pesticide residues in water and other food samples with higher matrix interferences.
Advances in the Use of Educational Robots in Project-Based Teaching

– Educational robots can serve as smart, mobile and tangible learning objects which can explicitly represent knowledge through actions and engage students through immersion and instant feedback. As pedagogical background, we employ the elements of Norman’s foundational theory of action and the Internet-of-Things Supported Collaborative Learning (IoTSCL) paradigm, which is based on constructivism. We describe the application of educational robots in project-based teaching at the university course. Positive relationship between successful implementation of robotics project and assimilation of theoretical knowledge has been established.
TIKHONOV REGULARIZATION ALGORITHM FOR PSEUDOMONOTONE VARIATIONAL INEQUALITIES

In general, the invention is directed to techniques for reducing deformation of tape in data tape cartridges during storage to promote dimensional stability and increased tape longevity. The techniques involve controlling the winding tension applied to a tape during a final winding pass prior to unloading a data tape cartridge containing the tape from a drive. Excessive winding tensions can produce strain and compression on a tape pack, causing the tape to deform over time. Applications of reduced winding tension during the final pass provide reduced tape pack tension during periods in which the data tape cartridge is not used.
Gender Equality in Environmental Issues for Achieving Sustainable Peace and Security in Nigeria

: This paper examines gender equality in environmental issues for achieving sustainable peace and security in Nigeria. The study adopts an ex-post facto research design. The findings confirm the age-long devastating effects of human exploitation of land and its resources. It discovers that enhanced peace and security (proxied by defense expenditure) leads to improved environment (reduced Co2 emissions) and that gender equality improves environment as a result of reduction in Co2 emissions due to gender mainstreaming on environmental management. Similarly, it also discovers that increase in the quality of governance which is control for corruption [CC]) will decrease Co2 emissions and indicates that good governance leads to reduced Co2 emissions and thus, better environment but on the contrary, age index leads to an increase in Co2 emissions. Since the moderating effects of environmental impact assessment curtails Co2 emissions from high industrialization, environmental impact assessment should be mandatory for every firm that would be established. Also, government should increase defense budget, design new industrial policies, ensure gender mainstreaming, intensify anti-corruption fight and enact environmental sustainability laws to reduce Co2 emissions, and improve environment with the ultimate target of attaining peace and security in Nigeria.
Extensive Studies on X-Ray Diffraction of Green Synthesized Silver Nanoparticles

Silver nanoparticle preparation and X-ray diffraction studies are reported in this paper. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and flammable. This paper deals with a cost effective and environment friendly technique for green synthesis of silver nanoparticles from silver nitrate solution by co-precipitation using the leaf extract of different species of Ocimum which acts as reducing and capping agent. The important ingredients responsible for the formation of silver nanoparticles present in the leaf extract are triterpenes, flavonoids and eugenol. Wide range of experimental conditions has been adopted in this process and its X-ray diffraction characterizations have been studied. The average crystalline size was 12 nm. The particle size and strain which were calculated using Williamson-Hall equation were 12.3 and 0.3688 respectively. The dislocation density was 7.9 × 10 14 m − 2 .
Mobile Data Modeling in Human Body “Network” Bell’s Palsy Case Study

—T he mysterious Path physiology of Bell's palsy sometimes prevents doctors to understand this disease. A fine diagnostic and an enhanced recovery surveillance are crucial for physicians to deeply be aware of the disease mechanisms. Moreover, the analyses of the patients' states may lead to the proposition of new strategies to cure the illness. This paper attempts to supervise the patients’ state evolution through the modeling of the facial nerve stream as a moving object circulating into the facial nerve “network”. Its progression through this latter, gives indication about patients’ recovery advancement and the disease behavior. We also propose, in this work, an algorithm based on graph matching concepts and a visualization algorithm able to show the recovery process in time. As a result, we obtain a graph, tracking the facial nerve stream. Then, physicians can observe the recovery progress. Hence, identifing the occurrence of conduction problem preventing it.
Canine cutaneous tumors in Sriracha district, Chonburi province, Thailand: a retrospective analysis of relative frequency and risk factors

A retrospective epidemiological study was conducted to identify a relative frequency of canine cutaneous tumors between January 2018 - December 2019 across Sriracha district, Chonburi province, Thailand and demonstrated the associations between age, sex, neuter status, breed types, anatomical locations, and body weight with skin tumors diagnosis. A total of 94 canine biopsy specimens according to 87 dogs were submitted for histopathological classification. The highest relative frequencies in this study were mast cell tumors (19.1%), followed by melanoma (8.5%), lipoma (7.4%), and histiocytoma (6.4%). The most frequent locations of tumor were found at limbs (24.4%), head (23.5%), trunk and flank (18.3%), and perineum (13.9%). A single type of cutaneous tumor was more regularly found than multiple types. The risk of developing cutaneous tumors increased significantly in the large-breed dogs (greater than 20 kg) compared to medium- and small-breed dogs. Male dogs had 5.28 times of the odds having tumors compared to female dogs ( P =0.002). Moreover, the occurrence of skin tumors is more common in elderly dogs. Our findings serve as a useful baseline information for regional veterinar ians to establish a preliminary diagnosis of canine cutaneous tumors.
Downlink Energy Efﬁciency Power Allocation for OFDM-based Aerial Systems with Limited Satellite Backhaul

—Emergency communications can beneﬁt from the integrated aerial-satellite systems due to the frequent Line Of Sight (LOS) access for User Equipments (UEs) and the robust satellite backhaul. This paper addresses an energy efﬁciency power allocation problem for a OFDM-based aerial system with limited satellite backhaul. Due to the non-convex backhaul capacity limit, the optimization problem is solved in two steps. Firstly, a non-negative parameter is introduced to convert the objective function to an equivalent convex form according to the fractional programming. Then, the optimal parameter for maximum Energy Efﬁciency (EE) without total power and backhaul capacity constraints is obtained. Secondly, by proving that the derivative of R ( P tot ) is equal to the above introduced parameter, which is decreasing in total power limit, P tot , these two constraints can be transformed into a lower bound on the parameter through geometric interpretation. Thus, an energy efﬁciency power allocation algorithm is proposed. Finally, numerical results show that the circuit power, total power limit and backhaul capacity limit have effect on the system EE.
Influence of third harmonic injection on modular multilevel converter-based high-voltage direct current transmission systems

: Whilst third harmonic injection is extensively used in modular multilevel converter (MMC) control, its significant advantages over sinusoidal modulation have not been fully explored. This study evaluates the influence of third harmonic injection on system power losses, submodule (SM) capacitance, circulating current, and fault current and mathematical models are derived. Station conduction losses are reduced by 11%, yielding higher efficiency and lowering cooling system capacity. The SM capacitance is reduced by 24%, which significantly lowers the capital cost, weight, and volume of the station converter. Additionally, the phase energy variation is reduced by around 18%, which benefits circulating current control. Due to the lower AC currents, the semiconductor current stresses are correspondingly reduced. In addition to the performance improvement in normal operation, the third harmonic injection reduces the DC fault currents by 13.4% and thus the fault current stresses on semiconductors and DC circuit breakers are lowered. Simulation of a point-to-point high-voltage direct current system demonstrates the effectiveness of the above analysis.
MIXED LOCATION SCALE MODEL 2

We present a mixed-effects location scale model (MELSM) for examining the daily dynamics of affect in dyads. The MELSM includes person and time-varying variables to predict the location, or individual means, and the scale, or within-person variances. It also incorporates a sub-model to account for between-person variances. The dyadic specification can accommodate individual and partner effects in both the location and the scale components, and allows random effects for all location and scale parameters. All covariances among the random effects, within and across the location and the scale are also estimated. These covariances offer new insights into the interplay of individual mean structures, intra-individual variability, and the influence of partner effects on such factors. To illustrate the model, we use data from 274 couples who provided daily ratings on their positive and negative emotions toward their relationship – up to 90 consecutive days. The model is fit using Hamiltonian Monte Carlo methods, and includes subsets of predictors in order to demonstrate the flexibility of this approach. We conclude with a discussion on the usefulness and the limitations of the MELSM for dyadic research.
SACS: A Self-Adaptive Checkpointing Strategy for Microkernel-Based Intermittent Systems

Intermittent systems are usually energy-harvesting embedded systems that harvest energy from ambient environment and perform computation intermittently. Due to the unreliable power, these intermittent systems typically adopt different checkpointing strategies for ensuring the data consistency and execution progress after the systems are resumed from unpredictable power failures. Existing checkpointing strategies are usually suitable for bare-metal intermittent systems with short run time. Due to the improvement of energy-harvesting techniques, intermittent systems are having longer run time and better computation power, so that more and more intermittent systems tend to function with a microkernel for handling more/multiple tasks at the same time. However, existing checkpointing strategies were not designed for (or aware of) such microkernel-based intermittent systems that support the running of multiple tasks, and thus have poor performance on preserving the execution progress. To tackle this issue, we propose a design, called self-adaptive checkpointing strategy (SACS), tailored for microkernel-based intermittent systems. By leveraging the time-slicing scheduler, the proposed design dynamically adjust the checkpointing interval at both run time and reboot time, so as to improve the system performance by achieving a good balance between the execution progress and the number of performed checkpoints. A series of experiments was conducted based on a development board of Texas Instrument (TI) with well-known benchmarks. Compared to the state-of-the-art designs, experiment results show that our design could reduce the execution time by at least 46.8% under different conditions of ambient environment while maintaining the number of performed checkpoints in an acceptable scale.
Canopy: A CNFET-based Process Variation Aware Systolic DNN Accelerator

Although systolic accelerators have become the dominant method for executing Deep Neural Networks (DNNs), their performance efficiency (quantified as Energy-Delay Product or EDP) is limited by the capabilities of silicon Field-Effect Transistors (FETs). FETs constructed from Carbon Nanotubes (CNTs) have demonstrated > 10 × EDP benefits, however, the processing variations inherent in carbon nanotube FETs (CNFETs) fabrication compromise the EDP benefits, resulting > 40% performance degradation. In this work, we study the impact of CNT process variations and present Canopy, a process variation aware systolic DNN accelerator by leveraging the spatial correlation in CNT variations. Canopy co-optimizes the architecture and dataflow to allow computing engines in a systolic array run at their best performance with non-uniform latency, minimizing the performance degradation incurred by CNT variations. Furthermore, we devise Canopy with dynamic reconfigurability such that the microarchitectural capability and its associated flexibility achieves an extra degree of adaptability with regard to the DNN topology and processing hyper-parameters (e.g., batch size). Experimental results show that Canopy improves the performance by 5.85 × (4.66 ×) and reduces the energy by 34% (90%) when inferencing a single (a batch of) input compared to the baseline design under an iso-area comparison across seven DNN workloads.
Layerwise Disaggregated Evaluation of Spiking Neural Networks

Spiking Neural Networks (SNNs) have attracted considerable attention due to their suitability to processing temporal input streams, as well as the emergence of highly power-efficient neuromorphic hardware platforms. The computational cost of evaluating a Spiking Neural Network (SNN) is strongly correlated with the number of timesteps for which it is evaluated. To improve the computational efficiency of SNN evaluation, we propose layerwise disaggregated SNNs (LD-SNNs), wherein the number of timesteps is independently optimized for each layer of the network. In effect, LD-SNNs allow for a better allocation of computational effort across layers in a network, resulting in an improved tradeoff between accuracy and efficiency. We propose a methodology to design optimized LD-SNNs from any given SNN. Across four benchmark networks, LD-SNNs achieve 1.67-3.84x reduction in synaptic updates and 1.2-2.56x reduction in neurons evaluated. These improvements translate to 1.25-3.45x faster inference on four different hardware platforms including two server-class platforms, a desktop platform and an edge SoC.
Exploiting successive identical words and differences with dynamic bases for effective compression in Non-Volatile Memories

Emerging Non-volatile memories are considered as potential candidates for replacing traditional DRAM in main memory. However, downsides like long write latency, high write energy, and low write endurance make their direct adoption in the memory hierarchy challenging. Approaches that reduce the number of bits written are beneficial to overcome such drawbacks. In this direction, we propose a compression technique that reduces overall bits written to the NVM, thus improving its lifetime. The proposed method, SIBR, compresses the incoming blocks to PCM by either eliminating the words to be written or by reducing the number of bits written for each word. For the former, words that have either zero content or are identical to consecutive words are not written. The latter is done by computing the difference of each word with a base word and storing only the difference (or delta) instead of the full word. The novelty of our contribution is to update the base word at run-time, thus achieving better compression. It is shown that computing the delta with a dynamically decided base compared to a fixed base gives smaller delta values. The dynamic base is another word in the same block. SIBR outperforms two state-of-the-art compression techniques by achieving a fairly low compression ratio and high coverage. Experimental results show a substantial reduction in bit-flips and improvement in lifetime.
A Charge Domain P-8T SRAM Compute-In-Memory with Low-Cost DAC/ADC Operation for 4-bit Input Processing

This paper presents a low cost PMOS-based 8T (P-8T) SRAM Compute-In-Memory (CIM) architecture that efficiently per-forms the multiply-accumulate (MAC) operations between 4-bit input activations and 8-bit weights. First, bit-line (BL) charge-sharing technique is employed to design the low-cost and reliable digital-to-analog conversion of 4-bit input activations in the pro-posed SRAM CIM, where the charge domain analog computing provides variation tolerant and linear MAC outputs. The 16 local arrays are also effectively exploited to implement the analog mul-tiplication unit (AMU) that simultaneously produces 16 multipli-cation results between 4-bit input activations and 1-bit weights. For the hardware cost reduction of analog-to-digital converter (ADC) without sacrificing DNN accuracy, hardware aware system simulations are performed to decide the ADC bit-resolutions and the number of activated rows in the proposed CIM macro. In addition, for the ADC operation, the AMU-based reference col-umns are utilized for generating ADC reference voltages, with which low-cost 4-bit coarse-fine flash ADC has been designed. The 256×80 P-8T SRAM CIM macro implementation using 28nm CMOS process shows that the proposed CIM shows the accuracies of 91.46% and 66.67% with CIFAR-10 and CIFAR-100 dataset, respectively, with the energy efficiency of 50.07-TOPS/W.
Synthetic Clothing and the Problem With Odor

Although polyester is well known for smelling strongly after wear, little is known about the propensity of nylon to retain and emit body odor. In this study, we investigated whether odor intensity differed between nylon and polyester fabrics. A secondary aim was to compare odor on fabrics frozen prior to sensory assessment with fabrics stored at room temperature. Eight participants wore T-shirts with fabrics in the underarm. Odor intensity was rated by 13 assessors. Odor reduction rate (ORR) was measured using ISO 17299-3. Overall, no differences were found in odor intensity between nylon and polyester. Any differences found between the two fabrics were likely dependent on the individual who wore the fabric. The ORR was higher for nylon than polyester, indicating that nylon absorbed more odorants. There was some evidence to suggest that odor intensity could increase on nylon fabrics stored at room temperature, but this was less apparent for polyester.
Cotranscription, Deduced Primary Structure, and Expression of the Chloroplast-encoded rbcL and rbcS Genes of the Marine Diatom Cylindrotheca sp. Strain N1*

The primary structure of ribulose- 1,5-b:sphosphate carboxylase/oxygenase from the marine diatom Cylin- drotheca sp. strain N1 has been determined. Unlike higher plants and green algae, the genes encoding the large and the small subunits of ribulose-1,5-bisphos-phate carboxylase/oxygenase are chloroplast-encoded and closely associated (Hwang and Tabita, 1989). The rbcL and rbcS genes in strain N1 are cotranscribed and are separated by an intergenic region of 46 nucleotide base pairs. Ribosome binding sites and a po- tential promoter sequence were highly homologous to previously determined chloroplast sequences. Compar- ison of the deduced primary structure of the diatom large and small subunits indicated significant homol- ogy to previously determined sequences from bacteria; there was much less homology to large and small sub- units from cyanobacteria, green algae, and higher plants. Although high levels of recombinant diatom large subunits could be expressed in Escherichia coli, the protein synthesized was primarily insoluble and incapable of forming an active hexadecameric enzyme. Edman degradation studies indicated that the amino terminus of the large subunit isolated from strain N1 was blocked, suggesting that the mechanism responsi- ble for processing and subsequent assembly of large and small subunits resembles the situation found with other eucaryotic ribulose-1,5-bisphosphate carboxyl-aseloxygenase proteins,
Genomics and localization of the Arabidopsis DHHC-CRD S-acyltransferase protein family

Protein lipid modification of cysteine residues, referred to as S-palmitoylation or S-acylation, is an important secondary and reversible modification which regulates membrane association, trafficking and function of target proteins. This enzymatic reaction is mediated by protein S-acyl transferases (PATs). Here, the phylogeny, genomic organization, protein topology, expression and localization pattern of the 24 PAT family members from Arabidopsis thaliana is described. Most PATs are expressed at ubiquitous levels and tissues throughout the development while few genes are expressed especially during flower development preferentially in pollen and stamen. The proteins display large sequence and structural variations but exhibit a common protein topology which is preserved in PATs from various organisms. Arabidopsis PAT proteins display a complex targeting pattern and were detected at the endoplasmatic reticulum, Golgi, endosomal compartments and the vacuolar membrane. However, most proteins were targeted to the plasma membrane. This large concentration of plant PAT activity to the plasma membrane suggests that the plant cellular S-acylation machinery is functionally different compared to that of yeast and mammalians. mainly targeted to the PM, indicating that the plant S-acylation machinery has a different organization and function compared to the mammalian and yeast PAT machinery.
Income Convergence across Nations and Regions in East Asia 

Using the Gross Regional Domestic Product data for 10 East Asian countries, this study shows that East Asia as a whole tends to converge to each other in terms of per capita income. If Northeast Asia is separately considered, there is far stronger evidence in favor of real growth convergence. This result suggests that the prospect for furthering economic and monetary integration in East Asia is not so gloomy. Despite such convergence trend, however, there are still relatively wider income disparities among regions and nations in East Asia than within Europe, suggesting that a common effort to reduce the income gap is needed for deeper integration.