Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation of LiMn2O4 Graphene Hybrid Nanostructure by Combustion Synthesis and Their Electrochemical Properties

The LiMn2O4 graphene hybrid cathode material has been synthesized by spray drying combustion process. The spinel structure cubic phase LiMn2O4 graphene hybrid material was prepared by spray drying process at 120 °C and subsequent heat treatment at 700 °C for 1 hour. The result indicates that the spinel shaped LiMn2O4 particles wrapped with graphene sheets were formed with particle size in the range of 60–70 nm. The charge-discharge measurement indicates that the LiMn2O4 graphene hybrid material shows an improved discharge capacity of 139 mAh/g at 0.1C rate. The pristine LiMn2O4 nano crystals present only about 132 mAh/g discharge capacity. The LiMn2O4 graphene hybrid samples show good cyclic performance with only 13% of capacity fading in 30 cycles when compared to the pristine LiMn2O4 that shows 22% of capacity fading in 30 cycles. The capacity retention of the LiMn2O4 graphene hybrid samples is about 10% higher than the pristine cycle after 30 cycles.
2- AND 3-D SEISMIC MODELLING: A VISUAL APPROACH

Reverse Time Migration (RTM) is among the most indicated tools for depth imaging of complex geological structures. Its assumptions are simple enough to make it recommended in cases where severe lateral velocity variations are present. However, its traditional approach, based on depth migrating of each and every common shot gather, not rarely demands immense computational efforts. In order to make RTM projects feasible, some authors have proposed alternative schemes in which multi sources records are migrated. In this work we exhibit the result obtained from depth migrating of a multi source record generated summing several common shot gathers of a seismic acquisition simulation on two models. One of the most important factors to researchers that develop algorithms applied to seismic modeling and wave propagation is the visualization of the results in an easy and friendly environment. The academic research groups that can’t afford the traditional software used by the oil industry are, in general, obliged to develop its own solutions to visualize its results, mainly when we are dealing with 3D environment. Another objective of this work is to present results gotten with computational routines developed in FORTRAN 90 for 2and 3-D seismic modeling using the finite difference method and to show some results of seismic wave propagation using commercial software of reduced cost. It were used the North Cuban (Miró, 2006) and SEG/EAGE velocity models to perform the seismic modeling.
H2O/D2O Contrast Variation for Ultra-Small-Angle Neutron Scattering to Minimize Multiple Scattering Effects of Colloidal Particle Suspensions

This study investigated the use of solvent contrast (H2O/D2O ratio) as a means to optimize the ultra-small-angle neutron scattering (USANS) signal. By optimizing the signal, it was possible to reduce the undesirable effects of coherent multiple scattering while still maintaining a measurable scattered intensity. This result will further enable the use of USANS as a probe of the interactions between colloidal particles and their structures within concentrated suspensions as well as particle dispersion/aggregation. As a model system, we prepared silica colloidal particle suspensions at different solid concentrations. USANS curves were measured using the classical Bonse–Hart double crystal diffractometer while varying the scattering length density of the aqueous phase, thus varying the contrast to the silica particles. As a means of assessing the impact of multiple scattering effects on different q-values, we analyzed the scattered intensity at different contrasts at three different q values. The data were then used to determine the match point of the silica particle suspensions from the expected square root dependence of the scattered intensity with solvent composition, to analyze any differences associated with the solid concentration change, and to determine the optimum H2O/D2O ratio in terms of high transmission (TSAS > 80%) and high enough scattering intensity associated with the contrast of the system. Through this investigation series, we confirmed that adjusting the contrast of the solvent (H2O/D2O) is a good methodology to reduce multiple scattering while maintaining a strong enough scattering signal from a concentrated suspension of silica particles for both USANS and rheometric USANS (rheo-USANS) experiments.
Clamping of DNA shuts the condensin neck gate

Condensin is a Structural Maintenance of Chromosomes (SMC) complex needed for the compaction of DNA into chromatids during mitosis. Lengthwise DNA compaction by condensin is facilitated by ATPase-driven loop extrusion, a process that is believed to be the fundamental activity of most, if not all SMC complexes. In order to obtain molecular insights, we obtained cryo-EM structures of yeast condensin in the presence of a slowly-hydrolysable ATP analogue and linear, as well as circular DNAs. The DNAs were shown to be “clamped” between the engaged heterodimeric SMC ATPase heads and the Ycs4 subunit, in a manner similar to previously reported DNA-bound SMC complex structures. Ycgl, the other non-SMC subunit was only flexibly bound to the complex, while also binding DNA tightly, and often remaining at a distance from the head module. In the clamped state, the DNA is encircled, or topologically entrapped, by the kleisin Brnl and the two engaged head domains of Smc2 and Smc4, and this tripartite ring is closed at all interfaces, including at the neck of Smc2. We show that the neck gate opens upon head engagement in the absence of DNA, but it remains shut when DNA is present. Our work demonstrates that condensin and other SMC complexes go through similar conformations of the head modules during their ATPase cycle. In contrast, the behaviour of the Ycgl subunit in the condensin complex might indicate differences in the implementation of the extrusion reactions and our findings will constrain further mechanistic models of loop extrusion by SMC complexes. SIGNIFICANCE STATEMENT DNA needs to be compacted dramatically to fit into nuclei and during cell division, when dense chromatids are formed for their mechanical segregation, a process that depends on the protein complex condensin. It forms and enlarges loops in DNA through loop extrusion. Our work resolves the atomic structure of a DNA-bound state of condensin in which ATP has not been hydrolysed. The DNA is clamped within a compartment that has been reported previously in other SMC complexes, including Rad50, cohesin and MukBEF. With the caveat of important differences that we also uncovered, it means that all SMC complexes cycle through at least some similar states and undergo similar conformational changes in their head modules, while hydrolysing ATP and translocating DNA.
Spectral Clustering and Vantage Point Indexing for Efficient Data Retrieval

Data mining is an essential process for identifying the patterns in large datasets through machine learning techniques and database systems. Clustering of high dimensional data is becoming very challenging process due to curse of dimensionality. In addition, space complexity and data retrieval performance was not improved. In order to overcome the limitation, Spectral Clustering Based VP Tree Indexing Technique is introduced. The technique clusters and indexes the densely populated high dimensional data points for effective data retrieval based on user query. A Normalized Spectral Clustering Algorithm is used to group similar high dimensional data points. After that, Vantage Point Tree is constructed for indexing the clustered data points with minimum space complexity. At last, indexed data gets retrieved based on user query using Vantage Point Tree based Data Retrieval Algorithm. This in turn helps to improve true positive rate with minimum retrieval time. The performance is measured in terms of space complexity, true positive rate and data retrieval time with El Nino weather data sets from UCI Machine Learning Repository. An experimental result shows that the proposed technique is able to reduce the space complexity by 33% and also reduces the data retrieval time by 24% when compared to state-of-the-art-works.
Digital Image Transmission with Polar Codes and Median Filtering

In digital images, different bits can carry different degrees of importance. Therefore, unequal error protection (UEP) is quite often incorporated into the transmission of digital images. The so-called "protection’ is achieved via error control coding (ECC), for which the most investigated ECC class in recent years - namely, polar codes - are adopted in this work. One key issue with polar codes is code construction - determination of frozen bit-channels and information bit-channels. Moreover, for UEP, the order of the information bit-channels according to which the various bits in image pixels are to be placed needs to be determined. One specific ordering scheme is proposed in this paper and compared to an existing method. One phenomenon observed in polar decoding is that whenever there occurs an erroneously decoded bit, the succeeding bits are also likely to become erroneously decoded. In terms of visual quality, this problem translates into continous line-segments of obviously wrong lightness. To counter this problem, the technique of median filtering combined with pixel-interleaving is adopted in this work. It turns out that our scheme produces good results, in terms of the PSNR (peak signal-to-noise ratio) and the visua quality of the recovered images.
Greedy Features Quantity Selection Method from Multivariate Time Series Data for Customer Classification

In recent years, toward the realization of the Internet of Things (“IoT”) society, related technologies have been developed and various electronic devices are being connected to the network. Even in companies that provide such kinds of products and services, it is possible to collect usage histories of their customers. If the companies can appropriately analyze the usage history data, it is useful for their marketing activities. However, in general, device usage histories are multivariate time-series data, and it is not obvious how to construct a feature space for customer classification and clustering. Therefore, this paper proposes a method to automatically select feature quantities characterizing the properties of customers using machine learning. We apply this method to real data and show its effectiveness.
Performance Evaluation of DOA Estimation Using Compressed Sensing with Fast Fourier Transform

This paper deals with the method of applying compressed sensing to DOA (Direction-Of-Arrival) estimation. To make use of multiple snapshots of array received data, we introduce FFT (Fast Fourier Transform) into the compressed sensing. Through computer simulation, we evaluate the performance of compressed sensing with FFT and show that the multiple snapshots are effectively utilized for DOA estimation by compressed sensing.
Structural damage identification of offshore wind turbines: A two‐step strategy via FE model updating

This study proposes a two‐step strategy for damage identification of offshore wind turbines via Finite Element (FE) model updating. In this methodology, the first step identifies the damaged component(s) using a verified global mathematical model of the offshore wind turbine under operational wind and wave loading. Damaged components can be the tower, a certain blade, or the foundation. Natural frequencies and mode shapes obtained from operational modal analysis are used to formulate the objective function for deterministic model updating. With the identified damaged component(s) in the first step, the second step of the strategy focuses on exact damage localization and quantification of the damaged component(s). To this end, an FE model of a baseline 5 MW monopile offshore wind turbine is established using ANSYS. Wind and wave loading are applied to simulate the structural responses under different damage scenarios. In additional to natural frequencies and mode shapes, mode shape curvatures obtained in the second step are included in the objective function. Results indicate that the proposed methodology can correctly identify most structural damage on the offshore wind turbines using operational data. The proposed two‐step damage identification strategy can circumvent the requirement of intensive computation due to full model updating of offshore wind turbine models and thus greatly improve the efficiency in real application.
Radiofrequency thermocoagulation for the treatment of trigeminal neuralgia

Although microvascular decompression (MVD) should be considered as the first-line treatment for classic trigeminal neuralgia (TN) owing to neurovascular compression of the trigeminal nerve, an increasing number of surgeons prefer radiofrequency thermocoagulation (RFT). RFT is a Gasserian ganglion-level ablative intervention that may achieve immediate pain relief for TN. It is used for emergency management when MVD is not suitable for the patient. As the gold surgical standard of classic trigeminal neuralgia, MVD has the advantage of longer efficacy. However, there are currently no high-quality controlled trials to evaluate the efficacy of MVD and RFT. For the present systematic review, the PubMed, Embase and Cochrane databases (all entries up until July 31, 2020) were searched to identify studies related to RFT in order to provide valuable information for clinical decision-making. The efficacy of the RFT method was evaluated in terms of the initial pain relief percentage, recurrence rate and follow-up time. Furthermore, the incidence rate of various postoperative complications was retrieved. RFT was used for a wider range of applications than MVD, including use for primary (owing to neurovascular compression of the trigeminal nerve), idiopathic and secondary (due to primary neurological diseases) TN, and provided a high rate of initial pain relief and long-term pain control. Although this method has several side effects, the incidence of complications could be reduced by precise cannulation. Furthermore, the complications that occurred were not permanent. Thus, RFT is a safe and effective minimally invasive method of pain relief for patients with TN.
Formulation and Characterization of Fluconazole as Topical Gel by Porous Microparticle Based Drug Delivery Systems

Controlled topical release drug delivery system for Fluconazole is potentially useful in improving drug deposition in the skin and reducing the incidence of adverse side effects. The purpose of the present experiment was to produce a topical gel system for the delivery of . Drug loaded microsponges (1–10) were formulated by an emulsion solvent diffusion method. Optimization of the microsponges was selected by drug loading efficiency. The optimized microsponges was formulated as topical gel and evaluated. The in vitro drug release, ex vivo drug deposition, primary skin irritancy study and in vivo antibacterial activity of loaded formulations were studied. The spherical and porous microparticles were obtained. Moreover, the optimized microsponge possess particle size, entrapment efficiency and production yield and of 84.49 µm, 72.21% and 39.40% respectively. Microsponge loaded gels indicated controlled release, no irritancy to rat skin and antifungal activity. An in vivo skin deposition study proved three fold higher retention in the stratum corneum layer as compared with plain gel. Microsponges-based gel formulations showed prolonged efficacy in a rat surgical wound model infected with Candida albicans . These results suggest that was stable in topical formulations and amplifying retention in the skin, indicating better potential of the delivery system for treatment of primary and secondary skin infections. The characteristics peak of the fluconazole is ~140. 68ºC The melting endothermic peak of fluconazole is shifted to ~139. 90ºC in the physical mixture with Ethyl cellulose, PVA. However, the minor changes observed in peak values of drugs are not indication of any potential incompatibility. FTIR spectra of the physical of drug and had all the characteristic and band values of pure fluconazole, confirming that all the functional groups in fluconazole are well preserved. The report clearly indicated absence of chemical interaction between the drug and polymer. Hence, the drug is compatible with all the excipients including polymer used in the present investigation.
Mutants in the Fe-S biogenesis component AtDRE2 develop twin embryos and are defective in DNA demethylation in the vegetative phase

Iron cofactors are essential for many cellular processes, frequently participating in electron transfer, catalytic reactions and gene regulation (1). Iron-Sulfur (Fe-S) clusters and the diferric tyrosyl radical cofactor are two types of Iron cofactors assembled by dedicated cellular machineries. In eukaryotes, Fe-S biogenesis is compartmentalized in organelles via pathways of prokaryotic origin and in the cytosol, via the CIA (Cytosolic Iron Sulfur Assembly) pathway. The CIA proteins are well-characterized in yeast and belong to three functional classes: 1. Electron transfer chain, composed of the diflavin reductase Tah18 (Top1T722A mutant Hypersensitive 18) and the Fe-S protein Dre2 (Derepressed for Ribosomal protein S14 Expression 2) (2); 2. Fe-S scaffold proteins including Npb35 (nucleotide binding protein 35) and Cdf1 (cytosolic Fe-S cluster deficient 1) (3); 3. Fe-S targeting complex proteins composed of four proteins: Nar1 (Nuclear architecture related 1), Cia1, Cia2, and Met18 (4). CIA pathway is responsible for the maturation of enzymes in the cytosol and in the nucleus. Some of these are known – for example, many DNA metabolism enzymes are Fe-S dependent (5) – but currently, a sizeable fraction of Fe-S proteins are unidentified (6). In addition to the CIA pathway, Tah18-Dre2 complex was recently found to function in diferric-tyrosyl radical formation, a cofactor required for the ribonucleotide reductase (7, 8). Although CIA proteins are highly conserved in eukaryotes, it has been difficult to reveal what are the cellular processes controlled by Fe-S clusters because
Hippocampal Neurons Model Implementation on FPGA

Hippocampus plays an important role in human cognitive function. In this paper, a modular idea is proposed. The modular implementation of hippocampal neurons model is described in detail, and the key problems of realizing hippocampal cortical neurons with FPGA (Field Programmable Gate Array) are explained. The proposed modeling algorithm based on the neuron model of FPGA is suitable for many channel models.
Investigation of Mineral Components and Antioxidant Properties of a Healthy Red Fruit: Cornelian Cherry (Cornus mas L.)

The mineral components of the foodstuff consumed by an individual are important in the growth and development of a human being. In recent years red fruits, because of their potential beneficial health effects, are getting attention of both consumers and manufacturers. One of the red fruits, Cornelian cherry (Cornus mas L.), was investigated in terms of both mineral components and antioxidant properties. The mineral components include calcium (Ca), iron (Fe), potassium (K), magnesium (Mg), and zinc (Zn) in this fruit were determined using flame atomic absorption spectrometry (FAAS). The antioxidant activity tests were applied to the extracts obtained using different solvents to examine the antioxidant properties of this fruit. Statistical analysis indicated that while the best results were obtained from acetone extracts, the lowest results were obtained from water extracts for all antioxidant activity tests (p<0.05). The best average values for DPPH and ABTS radical scavenging capacity, reducing power, total phenolic content and total flavonoid content in acetone extracts were found to be 1053.72±38.12 mg TEAC/100 g FW and 2907.34±152.05 mg TEAC/100 g FW, 5894.99±251.05 mg TEAC/100 g FW, 2979.25±69.40 mg GAE/100 g FW and 255.75±14.92 mg QE/100 g FW, respectively.
PENGARUH KNOWLEDGE MANAGEMENT TERHADAP KINERJA KARYAWAN

This research aims to know the influence of Knowledge Management onemployee performance on PT. Anzon Toyota Pontianak and to find out where Knowledge Management indicators that are most influential on employee performance. This research uses the IBM SPSS statistics application. The population in this research are the employee of PT. Anzon Toyota Pontianak. The sample used 40 respondents with using the saturated sample. Technique of data analysis in this research used simple linear regression analysis. Results of the study show that there is influence between variable Knowledge Management which consists of three indicators, namely Personal Knowledge, Job Procedure, and technology on employee performance with determinant of coefficients is 0.256. Data analysis showed that the Personal Knowledge is the indicators with the most biggest influence compared to other indicators.
SOFT SENSOR MODELS FOR A FRACTIONATION REFORMATE PLANT USING SMALL AND BOOTSTRAPPED DATA SETS

In refinery plants key process variables, like contents of process stream and various fuel properties, need to be continuously monitored using adequate on-line measuring devices. Such measuring devices are often unavailable or malfunction and, hence, laboratory assays which are irregular and time consuming and therefore not suitable for process control are inevitable alternatives. This research shows a comparison of different soft sensor models developed from a small industrial data set with soft sensor models developed from data generated by a bootstrap resampling method. Soft sensors were developed applying multiple linear regression, multivariable adaptive regression splines (MARSpline) and neural networks. The purpose of the developed soft sensors is the assessing of benzene content in light reformate of a fractionation reformate plant. The best results were obtained by the neural network-based model developed on bootstrapped data.
Analysis of a New Hybrid Sturdy MASH-11 Delta-Sigma Modulator

This paper presents a new two-stage hybrid sturdy MASH (SMASH) delta-sigma modulator (DSM) called HSMASH-11 DSM that can theoretically regains the 3 dB signal-to-noise and distortion ratio (SNDR) loss that a SMASH-11 DSM loses to a conventional MASH-11 DSM. In addition, the HSMASH-11 DSM still retains the insensitivity to the opamp gain that a SMASH-11 possesses. The HSMASH-11 DSM employs both inverting and non-inverting integrators in its structure. Mathematical and simulation results validate the efficiency of the proposed HSMASH-11 DSM.
Effect of Magnetically Treated Water on Precipitation of some Macro Elements in the Soil for Tomato Growth

This study was conducted to determine effect of magnetically treated water (MTW) on the precipitation of some macro elements in the soil for tomato growth. Magnetic flux densities used for treating the water were 124, 319 and 719 gauss (G) produced from electromagnet with direct current. A 1.0 litre of MTW was added to sandy loam in a bucket at 3 days interval for 45 days. Each treatment was replicated 3 times and a control experiment in which the soil was treated with 1.0 litre of non–magnetically treated water (NMTW) and replicated 3 times. The mean concentrations of calcium, potassium, sodium, nitrogen, phosphorus, organic matter and organic carbon for MTW treated using 719 G were 3.16 cmol/kg, 2.67 cmol/kg, 1.58 cmol/kg, 0.97 %, 2.39 mg/kg, 2.41 % and 1.39 %, respectively while the corresponding values for NMTW were 2.82 cmol/kg, 2.35 cmol/kg, 1.42 cmol/kg, 0.87 %, 2.26 mg/kg, 2.30 % and 1.32 %. MTW treated by 124 G also gave higher values of concentrations macro elements than the values from soil treated with NMTW. The influence of MTW by 124, 319, 719 G and NMTW on mean heights of tomato plant (growth) at 26 days after planting were 154.3, 178.6190. 3 and 137.1 mm while at 47 days the heights were 560.0, 556.4, 588.6 and 469.3 mm, respectively. Mean diameter of the tomato stem at 30 mm above soil level for 124, 319, 719 G and NMTW at 49 days after planting were 8.64, 7.99, 8.21 and 6.96 mm, respectively. Keywords: Magnetically treated water, macro elements, paired t-test, soil