Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Amendment with Composted Sludge On Soil Humic Acid Properties

The main physical and chemical properties of a composted mixture of sewage sludge and wood chips, the nonamended soil, and soils amended with two rates of the compost, in the presence or absence of barley, were determined. Humic acids (HAs) isolated from these materials were characterized by various methods including elemental analysis and Fourier Transform infrared (FTIR), fluorescence, and electron spin resonance spectroscopies. With respect to the nonamended soil HA, the compost HA was characterized by a prevalent aliphatic character, low oxygenated functional group content, high contents of S, N-containing groups and polysaccharide components, low free radical concentration, high molecular heterogeneity, and low degrees of ring polycondensation, polymerization and humification. Compost application at the low rate appeared to induce only limited modifications in the structural and chemical properties of HAs from amended soils, whereas apparent modifications of HA properties occurred where a high amendment rate was used. The absence or presence of barley cultivation appeared not to exert any measurable effect on the composition and properties of compost-amended soil HAs.
Controlling Melody Structures in Automatic Game Soundtrack Compositions With Adversarial Learning Guided Gaussian Mixture Models

The vastness of gaming plots and variety of environments in computer games require a large amount of labors in soundtrack compositions. Since human composers are expensive, artificial intelligence composing techniques have been proposed in several open-source projects. Current technologies have good performances at improvisations in short melody compositions, but face great challenges in industrial level automatic compositions of highly structured tracks for games. In this article, the overall structure specifying transitions and repetitions of melodies is given by human, and detailed contents like notes and rhythms are completed with a Gaussian mixture model (GMM) and generative adversarial nets (GAN). Different from recurrent neural networks, which are the mainstream automated melody generators, the GMM can be controlled to form structures because its latent space is often similar to the data space. A layered framework is devised where the basic layer composes melodies and high-level layers organize melodies according to long-term structures. In each layer, a Gaussian mixture generative model with constraints is constructed to compose candidate tracks, whereas another GMM network is trained in competition with the generator, such that optimal tracks from the generator are identified. Experiments show that the proposed framework has a high rate of composing acceptable soundtracks. Entropy curves calculated show that the composed tracks are more similar to game soundtracks than existing methods. In a user study, 11 out of 16 human criticizers favor the proposed compositions over the original GAN and recurrent neural networks.
Measuring of Sustainability Development Goals (SDGs) for Poverty Alleviation in Batu City, East Java Province - Indonesia

This study examines poverty eradication in Batu City, East Java Province Indonesia. This study aims to analyze the application of the SDG concept for poverty alleviation in the Batu City. It is projected that these results can be recommendations for the application of the SDGs in other regions in Indonesia. The population and sample used in this study were local government officials and the community who are directly involved in poverty alleviation activities, in total of 179 respondents. The analysis was carried out with descriptive qualitative using frequency analysis to find out the responses of respondents to the questionnaire. Next confirmatory statistical analysis is applied to strengthen the analysis results. SEM analysis with confirmatory is used to find out the variable indicators that can be used. The results of this study indicate that some of the goals proclaimed and agreed in the SDGs have been implemented by local governments, but still need to optimize the sustainability of economic development programs. So that local governments must be more intensive in implementing programs for equitable economic
Evaluation of Hotel Employees’ Satisfaction Using Ugc (User Generated Content)

: Job satisfaction is correlated with employees on job performance, guest satisfaction and implicitly with financial performance of a hotel. Previous studies showed that employees’ satisfaction when published online can influence guests booking intentions. We argue that it can influence and that it should be used to facilitate the human resource management process and prevent high turnover rates which are characteristic for hospitality. User generated content created a space for hotel employees to share their satisfaction/dis - satisfaction online with thousands of other jobseekers. This giant database could be used to improve working conditions, increase job satisfaction, and consequentially increase performance and guest satisfaction. This paper presents initial results from data collected from one of the most visited websites in the world glassdoor.com. In total, primary findings from more than 10.000 workers reviews were presented. Results show that culture and values and career opportunities are ranked as top variables that contribute to the overall job satisfaction. In addition, these two variables showed strong correlation with rating of senior management . This could be understood that employees their career opportunities and culture and values that prevail in organisation significantly associate with senior management.
Evaluation of a modified method of extraction, purification, and characterization of lipopolysaccharide (O antigen) from Salmonella Typhimurium

Background and Aim: Lipopolysaccharide (LPS) is an integral part of the outer cell membrane complex of Gram-negative bacteria. It plays an important role in the induction and stimulation of the immune system. Various LPS purification protocols have been developed. However, analysis of their efficacy is limited by contamination during downstream applications or the public health hazard of LPS. The aim of this study was to evaluate a modified method for extracting LPS as well as assess the purity of the extracted LPS by high-performance liquid chromatography (HPLC) analysis. Further, we evaluated its immunopotentiating function by measuring the relative RNA expression levels of splenic immune-related genes such as interleukin 1β (IL-1β) and interferon-γ (IFN-γ), after intramuscular injection of increasing concentrations of the extracted LPS in specific pathogen-free (SPF) chick. Materials and Methods: Isolation, identification, and serotyping of Salmonella Typhimurium were performed using chicken flocks. We then performed molecular typing of Salmonella isolates using conventional polymerase chain reaction (PCR). A new protocol for purification of LPS from Salmonella isolate (S. Typhimurium) was conducted. HPLC analysis of the extracted LPS in the current study was compared to existing methods. An in vivo study was performed to evaluate the ability of LPS to induce an immune response by measuring relative IFN-γ and IL-1β gene expression after injecting increasing concentrations of the extracted LPS into SPF chicks. Results: Isolation and serotyping revealed that Salmonella enterica was of the serovar Typhimurium. Confirmation was conducted by molecular typing through conventional PCR. Fractionation of the LPS extract by HPLC revealed a high degree of purity comparable with standard commercial LPS. These results demonstrate the high purity of extracted LPS based on our modified method using propanol and sodium hydroxide mixture. Intramuscular injection of the extracted LPS in 22 day-old SPF chicks, compared to the negative control, revealed significant upregulation of IFN-γ and slight downregulation of IL-1β. Conclusion: The new modified method can be used for high purity LPS extraction and demonstrates effective immunopotentiating activity.
Preparation and Photocatalysis Properties of TiO2/Graphene Nanocomposites

In this work, a novel photocatalyst with excellent photocatalytic activities was developed by the combination of TiO2 with graphene oxide (GO). GO was firstly prepared by the chemical oxidation of graphite through Hummers method and the subsequent dispersion and exfoliation in water. Then, GO and P25 nanoparticles (commercial TiO2) were used as raw materials to synthesize TiO2/graphene (TiO2/GE) nanocomposites by using a one-step solvothermal method. TEM images clearly showed that TiO2 nanomaterials (the size of about 15~20 nm) were distributed well onto the two-dimensional (2D) graphene sheets, indicating the formation of TiO2/GE nanocomposites. XRD results indicated that TiO2/GE nanocomposites exhibited TiO2 crystalline phase structure. Meanwhile, it was demonstrated from the methylene blue (MB) photodegradation results that TiO2/GE nanocomposites possessed excellent photocatalytic activities with potential applications.
Does a District-Vote Matter for the Behavior of Politicians? A Textual Analysis of Parliamentary Speeches

In most democracies, members of parliament are either elected over a party list or by a district. We use a discontinuity in the German parliamentary system to investigate the causal effect of a district-election on an MP’s conformity with her party-line. A district-election does not affect roll call voting behavior causally, possibly due to overall high adherence to party voting. Analyzing the parliamentary speeches of each MP allows us to overcome the high party discipline with regard to parliamentary voting. Using textual analysis and machine learning techniques, we create two measures of closeness of an MP’s speeches to her party. We find that district-elected members of parliament do not differ, in terms of speeches, from those of their party-peers who have been elected through closed party lists. However, both speeches and voting correlate with district characteristics suggesting that district-elections allow districts to select more similar politicians.
Development and Characterization of Vertically Stacked Tactile Sensor With Hollow Structure

In this study, a capacitive tactile sensor (CTS) that simultaneously supports high detection sensitivity and high spatial resolution with a hollow dielectric structure is reported. By vertically stacking two capacitors with intentionally misaligned electrodes among the capacitors, not only the normal and shear force but also the shear angle can be detected. A comprehensive fabrication procedure that advanced the existing solutions was developed in addition to its theoretical design and numerical evaluation. Results indicated that the proposed hollow CTS outperformed the referential solid CTS in detection sensitivity for both the normal (on average 31.660 pF/N under 0.5 N) and shear force (at least 5.61 times enhancement under 1.5 N) applications. The results also proved comparable shear angle detection accuracy to previously existing CTS. Additionally, the periodical variation of sensitivity enhancement along the shear angle was found and analyzed for the first time, which provided design guidance for the arrangement of the electrodes in the CTS regardless of its dielectric structure.
Efficient SSE With Forward ID-Privacy and Authentication in the Multi-Data-Owner Settings

Based on Sun et al.’s multi-client symmetric searchable encryption (SSE) scheme (at ESORICS 2016), and combining Zhao’s identity-concealed authenticated encryption (CCS 2016), a new SSE scheme with multi-data-owner functionalities is proposed. By setting two key generation centers, our scheme first implements multi-data-owner SSE. In particular, compared with Sun et al.’s scheme, the new scheme not only meets the same security requirements stated by them, but also further strengthens the securities of the same category relevant scheme by providing identity-concealment, authentication of data user to server and confidentiality of search token. The identity-concealment aims to provide privacy protection (Forward ID-Privacy) for data users by hiding their identity information, while the authentication is to resist the camouflage attack by applying certificate-based mechanism to our scheme. In particular, the confidentiality of the search token provides replay-attack-resistant by encrypting the plaintext search token generated by data user. While in other works, the adversary can employ the previously generated plaintext search tokens to force the server to perform the same search queries. Furthermore, by efficiency analysis, our scheme reaches almost the same level of efficiency as Sun et al.’s scheme.
Dynamic Gesture Recognition Based on Deep Learning in Human-to-Computer Interfaces

ABSTRACT Currently, gesture recognition provides a faster, simpler, convenient, effective and more natural way for human-computer interaction, which has been widely concerned. Gesture recognition plays an important role in real life. The manual feature extraction in traditional gesture recognition methods is time-consuming and strenuous. Moreover, in order to improve the accuracy of recognition, the quantity and quality of features to be extracted are required to be very high, which is a bottleneck for traditional gesture recognition methods. Therefore, we propose a deep learning method for dynamic gesture recognition in Human-to-Computer interfaces. An improved inverted residual network architecture is utilized as the basis of SSD (Single Shot MultiBox Detector) network for feature extraction. And the convolution structure of the auxiliary layer is predicted by using the inverse residual structure combining the cavity convolution. It uses multi-scale information, which can reduce the amount of calculation and parameters number. Transfer learning is used to optimize the trained network model so as to reduce the training time and make the model more convergent. Finally, experimental results show that the proposed method can recognize different gestures quickly and effectively.
Multiphysics and Multiobjective Design Optimization of High-Frequency Transformers for Solid-State Transformer Applications

This article proposes a multiphysics-based and multiobjective design optimization of high-frequency transformers (HFT) for solid-state transformer (SST) applications. Achieving an efficient SST, regardless of its topology, highly depends on the design optimization of its HFT design parameters. Also, a high-power-density. The proposed algorithm (based on time-harmonic electromagnetic, thermal, and fluid physics model coupling) minimizes the volume of the HFT, total cost as well maximizes its efficiency. A case study of <inline-formula><tex-math notation="LaTeX">$20 \text{ kW}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$10 \text{ kHz}$</tex-math></inline-formula> is investigated and its Pareto optimal solutions (POS) presented. The simulation results show the various dependencies of the design variables on the proposed objective functions which verifies effectiveness of the proposed algorithm. The Pareto optimal solutions (POSs) show that efficiencies above <inline-formula><tex-math notation="LaTeX">$99\%$</tex-math></inline-formula> can be achieved with appropriate selection of the design variables. From the POS, two case studies of the HFTs (referred to as <inline-formula><tex-math notation="LaTeX">$HFT_1$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$HFT_2$</tex-math></inline-formula> using <inline-formula><tex-math notation="LaTeX">$AMCC-100$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$AMCC-250$</tex-math></inline-formula> amorphous cores, respectively) are further investigated based on multiphysics numerical models. An experimental implementation of the optimized HFTs (<inline-formula><tex-math notation="LaTeX">$HFT_1$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$HFT_2$</tex-math></inline-formula>) is integrated with a self-tuned dual active bridge converter to validate their performance. The experimental measurements from the HFTs are in very good agreement with the optimization results.
Synthesis of silver nanoplates with controlled shapes by reducing silver nitrate with poly(vinyl pyrrolidone) in N-methylpyrrolidone

This article describes a simple approach to the synthesis of Ag nanoplates with controlled shapes by reducing silver nitrate (AgNO3) with poly(vinyl pyrrolidone) (PVP) in N-methylpyrrolidone (NMP). The hydroxyl end groups of PVP have been shown to serve as a mild reductant for the kinetically controlled synthesis of Ag nanoplates. Here, we demonstrated that Ag nanoplates with tunable size and aspect ratio could be formed with high yields in a kinetically controlled synthesis using NMP as the reaction medium. NMP plays a critical role in the formation and growth of the nanoplate morphology. The reaction time and weight ratio of PVP to AgNO3 could both be adjusted to permit the shape-controlled synthesis of Ag nanoplates, that is, with control over the nanoplate size and aspect ratio. Shape control permitted tuning of the localized surface plasmon resonance (LSPR) peaks of these Ag nanoplates over the visible and near-IR regions.
An Adaptive Direction-Dependent Polarization State Configuration Method for High Isolation in Polarimetric Phased Array Radar

High cross-polarization isolation (CPI) is crucial to the accurate polarization measurement using polarimetric phased array radar (PPAR). In this article, we propose an adaptive direction-dependent polarization state configuration (<inline-formula> <tex-math notation="LaTeX">$\text {A}{{\text {D}}^{{2}}}\text {PSC}$ </tex-math></inline-formula>) method to improve the polarization isolation. Compared with the conventional fixed polarization state of radiated wave whether it is linear, circular, or elliptical polarization state, our <inline-formula> <tex-math notation="LaTeX">$\text {A}{{\text {D}}^{{2}}}\text {PSC}$ </tex-math></inline-formula> approach configures the polarization state on basis of beam steering. To achieve the adaptive configuration of magnitude and phase of the dual-polarization antenna, an improved steepest descent algorithm is put forward. To facilitate the uniform representation for the polarization measurement application of PPAR, the universal expressions of intrinsic and measured backscatter matrices are derived for arbitrary polarization state. The dual-polarization dipole array is used to assess the priority of our proposed method. Compared with the conventional approaches, our approach could obtain higher CPI while being available for a larger scanning range. The configured CPI meets the specific polarization requirement for PPAR.
Adsorption des protéines sur les surfaces de couches minces de silice seules ou additivées de nanoparticules d'argent : impact sur les forces d'adhésion de Candida albicans

Dans de nombreux secteurs, l'adhesion microbienne sur les surfaces est la source de multiples impacts negatifs. Cette etape est consideree comme preliminaire au developpement de biofilm et peut etre influencee par la presence d'un film conditionnant engendre par l'adsorption des proteines sur la surface. Ainsi, les strategies visant une intervention au moment de la phase initiale d'adhesion representent une approche appropriee pour prevenir la bio-contamination des surfaces et necessitent une comprehension a l'echelle moleculaire. Dans ce contexte, les materiaux nanocomposites a base de nanoparticules d'argents (AgNPs) et de silice (SiO2) apparaissent comme des outils pertinents. Ce travail de these porte sur l'utilisation de substrats nanocomposites possedant une monocouche d'AgNPs exposees a leurs surfaces ou enterrees dans une matrice de SiO2plasma a une distance controlee de quelques nanometres de la surface afin d'explorer, d'une part l'adhesion de proteines modeles (Serum Albumine Bovine, DsRed et Fibronectine) et leurs changements conformationnels et d'autre part, la cinetique de detachement de la levure Candida albicans dans les differentes conditions. Les AgNPs sont bien connues pour leurs activites antimicrobiennes et presentent de plus, des proprietes optiques permettant de detecter des signatures moleculaires a leurs proximites. Suite a l'application de la spectroscopie Raman exaltee de surface en utilisant les couches nanocomposites a base d'AgNPs, la detection de trois conformations de la DsRed (proteine fluorescente rouge) adsorbee et deshydratee sur les substrats plasmoniques a ete possible. Les resultats obtenus montrent que les changements conformationnels des proteines avec une forte coherence interne sont reversibles. En parallele, nous avons evalue la dynamique d'organisation et le comportement de la SAB, de la Fn et de la DsRed en contact avec des couches minces de silice ou additivees d'AgNPs. Les mesures des angles de contact des gouttelettes de differentes concentrations proteiques ont montre une interaction hydrophile croissante avec la SiO2th thermique. L'hydrophobicite de surface est modifiee pour les substrats nanocomposites. L'epaisseur et les proprietes optiques des couches proteiques adsorbees ont ete evaluees par ellipsometrie spectroscopique. En fonction de la concentration de proteines dans solution les resultats montrent l'evolution d'une monocouche proteique non continue et non dense vers une monocouche plus compacte et plus complexe pour des concentrations elevees. [. ]
Studies of textile effluent discharges in Nigeria

Baseline studies were carried out on some textile factories in Nigeria, and the effluents were analysed for their pollution characteristics. The studies revealed that the wastewater from the factories were untreated and that high amounts of pollutants, as shown by the high values of pollution characteristics, were discharged from them daily. The pollutants, aggravated by the presence of free chlorine and toxic heavy metals, caused rapid depletion of dissolved oxygen leading to ’oxygen sag’ in the receiving water. These pollutants are known to destroy micro‐organisms stabilizing wastes in the receiving stream and leading to a reduction in the self‐purifying capacity of the stream.
An Importance Performance Analysis (IPA) of Tour Guide in Mainland China

China is opening up its door wider to the world to attract more and more people from all over the world to visit China. Owing to the diverse culture, possessing rich wonderful places with fantastic panoramic view, tourism industry in China is booming at an exponential rate. They are the axis of the whole travel experience and, to some; they are soul of the tourism industry. In certain instances they are considered the ‘beautiful angel’ who will provide the tourists with an unforgettable experience reflected through China’s beauty and hospitality. As the industry grows, so does the demand for capable tour guides. Tour guide is a significant component of tourism industry, and their performance is very crucial in the tourists’ satisfaction. The tourist guide service quality is able to directly affect the total tourist’s experience. However, tourists are lamenting that the guides are incompetent in their work performance which affect their satisfaction level. Hence, the aim of this study is to assess the influence of tour guide’s performance on people’s travel experience (and satisfaction) in China’s. The importance-performance analysis was used in the context of attributes of tour guide to describe the importance attributes of tour guide according to the consumer expectation and compare with customers satisfaction on these attributes to see whether they are satisfied with the services offered by tour guides in mainland China. Self-administrated questionnaire was developed from IPA instrument and distributed to Chinese tourists and international tourists. The findings of this study are expected to contribute in the improvement of tour guides performance through a standard document for tour guiding competences and training programs.