Miracle-dz/UniFAR-FTUs huggingface dataset:
Poly(3-hydroxybutyrate) (PHB) and Polycaprolactone (PCL) Based Blends for Tissue Engineering and Bone Medical Applications Processed by FDM 3D Printing

In the presented work, poly(3-hydroxybutyrate)–PHB-based composite blends for bone medical applications and tissue engineering are prepared and characterized. PHB used for the work was in two cases commercial and, in one case, was extracted by the chloroform-free route. PHB was then blended with poly(lactic acid) (PLA) or polycaprolactone (PCL) and plasticized by oligomeric adipate ester (Syncroflex, SN). Tricalcium phosphate (TCP) particles were used as a bioactive filler. Prepared polymer blends were processed into the form of 3D printing filaments. The samples for all the tests performed were prepared by FDM 3D printing or compression molding. Differential scanning calorimetry was conducted to evaluate the thermal properties, followed by optimization of printing temperature by temperature tower test and determination of warping coefficient. Tensile test, three-point flexural test, and compression test were performed to study the mechanical properties of materials. Optical contact angle measurement was conducted to determine the surface properties of these blends and their influence on cell adhesion. Cytotoxicity measurement of prepared blends was conducted to find out whether the prepared materials were non-cytotoxic. The best temperatures for 3D printing were 195/190, 195/175, and 195/165 °C for PHB-soap/PLA-SN, PHB/PCL-SN, and PHB/PCL-SN-TCP, respectively. Their mechanical properties (strengths ~40 MPa, moduli ~2.5 GPa) were comparable with human trabecular bone. The calculated surface energies of all blends were ~40 mN/m. Unfortunately, only two out of three materials were proven to be non-cytotoxic (both PHB/PCL blends).
Analysis of Land Use and Land Cover Changes in Owerri Municipal and Its Environs, Imo State, Nigeria (2005 – 2015)

Land use/land cover changes in Owerri Municipal and its environs which included Orogwe, Ubomiri, Emii, Uratta, Ihiagwa and Egbu were studied as being driven by rapid population growth for urbanisation. The study applied the digital technology of Remote Sensing and Geographic Information System (ARC GIS 9.3 Version software). These tools were implored to generate land use/land cover maps for the period; 2005, 2010 and 2015 and to determine the area in km2 of each of the six classes of land use/land cover types, the percentage change of the total area covered, accuracy of the overall classification including the Kappa coefficient, while a classification scheme was used to develop the classified land use/land cover maps. Also satellite imagery for the period (2005-2015) was imputed into the ENVI 4.5 software environment, composited, digitized and exported to the Arc. GIS where they were clipped with the study area. The extracted image of the study area was then exported back to the ENVI 4.5 environment for Arc.GIS environment in TIFF format. This was followed by a colour separation in the imagery repeated for all the raw satellite imagery. Image interpretation was done on ENVI 4.5 software based on a set of pixels of the Region Of Interest (ROI). Results are that Kappa coefficient values were high enough for the period of study with 0.9099, 0.9557 and 0.9685 for 2005, 2010 and 2015 respectively indicating a strong agreement between the classified maps and ground referenced information. Integrating GIS and satellite remote sensing with high spectral, spatial and temporal resolution at the local scale to develop urban environmental monitoring, effective land use planning and management of the current growth pattern were among others recommended.
Patterned Cu Nanoparticle Film for All-Cu Interconnection Without Chemical Mechanical Polishing Pretreatment

All-Cu interconnects with fine pitch scalability and excellent electrical performance are highly considered the next interconnection node for the coming era of chiplet integration. However, current all-Cu interconnection through Cu–Cu direct bonding relies much on expensive chemical mechanical polishing (CMP) processes to reduce surface roughness to several nanometers. Herein, Cu nanoparticle (CNP) film prepared by pulsed laser deposition (PLD) was successfully patterned into micro bumps of <inline-formula> <tex-math notation="LaTeX">$120 \mu \text{m}$ </tex-math></inline-formula> pitch and sintered at 160 °C–250 °C to form all-Cu interconnects without using CMP pretreatment. The fabricated bumps had a low Young’s modulus of only 1 GPa and could produce vertical collapse of several microns in bonding process, providing compliance with surfaces having high roughness and poor coplanarity. The bonded interconnects also exhibited excellent mechanical quality with shear strength <inline-formula> <tex-math notation="LaTeX">$>$ </tex-math></inline-formula>20 MPa at 160 °C, 15 MPa and <inline-formula> <tex-math notation="LaTeX">$>$ </tex-math></inline-formula>90 MPa at 250 °C, 20 MPa, which was superior to most reported Cu–Cu bonding using patterned nanomaterials. Patterning mechanism in PLD process involving incident characteristics of CNP flux, evolution of bump morphology was investigated and bump morphology’s influence on bonding properties was analyzed in detail. The strategy illustrated here could lead to develop a low-temperature, low-pressure assembly technique with less reliance on CMP for all-Cu interconnection.
Intelligent Reflecting Surface Backscatter Enabled Downlink Multi-Cell MIMO Networks

This paper proposes to leverage intelligent reflecting surface (IRS) backscatter to implement downlink communications for a multi-cell multiple-input multiple-output (MIMO) network, which represents a brand-new communication framework. In such a network, one active macro cell base station (MBS) is deployed for radiating energy signal, while each IRS acts as a small cell base station to realize its own information transmission by modulating and reflecting the signal from the MBS. Under this paradigm, we investigate two optimization problems, namely weighted sum rate maximization problem and max-min fairness problem, aiming at satisfying different communication requirements. To seek their optimal solutions, Lagrangian dual transform and alternate methods are employed to optimize the active beamforming vector at the MBS and the passive beamforming vectors at all the IRSs. Additionally, an element clustering scheme is developed to reduce computation and control complexity, in which each element cluster works like a unit and all clusters can collaborate to communicate with users. Extensive simulations are conducted to evaluate the achievable communication performance and to verify the feasibility of the proposed IRS backscatter enabled downlink multi-cell MIMO network.
Point Cloud Generation of Transparent Objects: A Comparison between Technologies

This paper proposes an approach to attract students to the study of Vision Systems to detect transparent materials, such as glass or plastic, through the comparison of videogame technologies, e.g. the Kinect Sensor, and more complex systems, such as Stereo Vision. Although the field of computer vision has advanced enormously in recent years, there are still problems when it comes to viewing transparent materials. Technologies such as the Kinect Sensor have been widely implemented in research before, but they lack the capabilities to detect transparent materials as well. A good alternative is the use of Stereo Cameras that can triangulate points from pictures with two perspectives. However, given that the Kinect is used in videogames and for hobbies, it represents a great area of opportunity to attract its intended public into research activities, as it could act as a catalyst to foster curiosity, mainly undergraduate students, into how technology intended for videogames can be applied for something as important as Computer Vision.
Green's function approach to investigate the excitation of surface plasmon polaritons in a nanometer-thin metal film

The two-dimensional magnetic-field Green's function for a nanometer-thin metal film embedded in a dielectric environment is constructed with the mode-expansion method. Explicit expressions are obtained for the Green's-function components related to the excitation of symmetric and antisymmetric surface-plasmon polariton (SPP) waves and out-of-plane propagating waves, respectively. The obtained expressions are used to study the power emitted by a magnetic dipole line source into the different radiation channels. For a wavelength of $\ensuremath{\lambda}=500$ nm the total emitted power is found to increase by a factor of three (the Purcell factor), with approximately 60% going into SPP waves when the source is placed directly on the surface of a 15-nm-thick silver film. Results obtained with and without including ohmic losses in the calculations are only negligibly different. The presented semianalytical approach allows for an exact analysis of the excitation of SPP waves on nanometer-thin metal films and may therefore find several applications within nanoplasmonics.
Pure qP-wave propagation in VTI media

The qP and qS-wave eikonal equations derived from the VTI wave equation show that in the pseudoacoustic approximation, their dispersion relations degenerate into a single one. Therefore, when using this dispersion relation for wave simulation, for instance by means of finite-difference approximations, both events are generated. To avoid the occurrence of the pseudo-S wave, the qP-wave dispersion relation alone needs to be approximated. This can be done with or without the pseudo-acoustic approximation. A Pade approximation with slightly unconventional numbers for the Pade coefficients led to the best approximation. An implementation of a low-rank approximation to this equation demonstrates that this can provide high-accuracy wavefields even in strongly anisotropic inhomogeneous media.
Enabling Efficient Spatio-Temporal GPU Sharing for Network Function Virtualization

By leveraging standard IT virtualization technology and Commercial-Off-The-Shelf (COTS) servers, Network Function Virtualization (NFV) decouples network functions from proprietary hardware devices for flexible service provisioning. But the potential of NFV is significantly limited by its performance inefficiency. With the unparalleled advantages of multi-core parallelism and high memory bandwidth, Graphics Processing Units (GPUs) are regarded as a promising way to accelerate Virtualized Network Functions (VNF). However, the special architecture of GPU brings new challenges to task scheduling and resource allocation. To this end, we propose a GPU oriented spatio-temporal sharing framework for NFV called Gost, aiming for GPU based VNF performance promotion. The execution order and GPU resource allocation (i.e., the number of threads) are considered in task scheduling to minimize the end-to-end latency for VNF flows. First, we formulate the task scheduling problem into a nonlinear programming form, and then transform it into an equivalent Integer Linear Programming (ILP) form. The problem is proved as NP-hard. We customize the classical list scheduling algorithm and propose a List Scheduling based Spatio-Temporal GPU sharing strategy (LSSTG), whose achievable worst-case performance is also formally analyzed. We practically implement Gost prototype, based on which extensive experiments verify the high performance efficiency of LSSTG compared to state-of-the-art in terms of latency and throughput.
Provenance and Paleoclimate Analysis of Sandstone from Meluhu Formation in Kendari, Southeast Sulawesi.

The Meluhu Formation consists of quartz sandstone, red shale, siltstone, and mudstone at the bottom part, and alternating black shale, sandstone, and thin limestone in the upper part. Petrographic components composition can reveal the litho-tectonic setting of a region. The composition of sandstone can be done by determining and counting the proportion of a quartz minerals, feldspar, and rock fragment from thin sections using petrographic analysis. This result can guide to depositional setting and paleoclimates of a region. The Provenance and paleoclimates studies of Meluhu Sandstone are still relatively new. The purpose of this study was to find out the provenance and paleoclimate of sandstone of Meluhu Formation which is exposed in 14 sites along Kendari and adjacent area. The method used to make petrographic observations followed by data processing using the point counting method. The sandstone in this study area was classified into sublitharenite, lithic arenite, arkose, subarkose, and greywacke. The origin of rock was interpreted as located in the recycled orogenic province, interior craton, and undissected arc. The paleoclimate that occurred in the formation of these siliciclastic rocks was arid to humid. Keywords: Meluhu Formation, provenance, paleoclimate, sandstone.
A survey on Audio-Visual Speech Recognition System

Speech is the most effective and vital form of communication between people and their surroundings. It can recognize nondeterministic audio along with given preponderance among decisions with a near probability by using an approach that makes advantage of image processing skills for lip reading. The idea of continuing research into the creation of an automatic voice recognition system, which is a positive approach to humancomputer interaction, inspired certain researchers. However, in actual use, the existing framework’s effectiveness is adversely impacted by the existence of an audial noisy environment, which makes it difficult to recognize actual speech. Due to this, AudioVisual Speech Recognition (AVSR) was developed in order to overcome these difficulties by utilizing both audio and video feeds. This paper is being taken down in order to describe the fundamental design of the different AVSR as well as how it has changed over time in various research projects. It also further distorts our impression of future audio visual speech recognition architectural designs.
Relação entre a Capacidade Social e o Desempenho Social das Empresas Brasileiras Mediada pela Responsabilidade Social Corporativa

Objetivo: Este estudo objetiva analisar a relação entre a capacidade social e o desempenho social, mediada pela responsabilidade social corporativa, no contexto das empresas brasileiras listadas na B3. Método: A pesquisa caracteriza-se como descritiva em relação a seu objetivo, quanto aos procedimentos é considerada como pesquisa aplicada a partir do levantamento de dados primários. Este estudo foi realizado com empresas de capital aberto do Brasil, por meio da aplicação de questionário aos gestores das empresas listadas na B3. As respostas obtidas por meio do questionário são provenientes da alta administração. Trata-se de uma pesquisa quantitativa em relação à abordagem do problema, sendo analisada por meio da modelagem de equações estruturais (MEE), com utilização do software SPSS AMOS versão 22. Resultados: A importância da capacidade social não é apenas uma consideração estratégica para obter bons resultados de desempenho social e RSC, é antes de tudo uma consideração primária e fundamental quando se trata do alcance dos objetivos sociais das empresas. Diante disso, este estudo comprova que existe uma relação entre a capacidade social e o desempenho social das empresas brasileiras mediada pela responsabilidade social corporativa. Esse caminho de mediação CS => RSC => DS possui um ß= 0,705, onde a CS e RSC explicam o DS em aproximadamente 93%. Contribuições: O estudo contribuiu à medida que esclarece, no teste de mediação, que a responsabilidade social corporativa medeia positivamente a relação entre a capacidade social e o desempenho social das empresas brasileiras. Somente integrar as partes interessadas nos processos decisórios e incluir suas necessidades na definição e realização dos objetivos sociais da organização não são suficientes para atender aos interesses de suas partes interessadas. Como implicação prática, as evidências da pesquisa empírica podem contribuir para elucidar discussões sobre a capacidade social auxiliar os gestores e diretores das empresas brasileiras a entender melhor o seu papel na distribuição de bens não financeiros.
Geometrically accurate real-time volumetric visualization of the middle ear using optical coherence tomography.

We introduce a novel system for geometrically accurate, continuous, live, volumetric middle ear optical coherence tomography imaging over a 10.9mm×30∘×30∘ field of view (FOV) from a handheld imaging probe. The system employs a discretized spiral scanning (DC-SC) pattern to rapidly collect volumetric data and applies real-time scan conversion and lateral angular distortion correction to reduce geometric inaccuracies to below the system's lateral resolution over 92% of the FOV. We validate the geometric accuracy of the resulting images through comparison with co-registered micro-computed tomography (micro-CT) volumes of a phantom target and a cadaveric middle ear. The system's real-time volumetric imaging capabilities are assessed by imaging the ear of a healthy subject while performing dynamic pressurization of the middle ear in a Valsalva maneuver.
Beamforming and Power Optimization for User Fairness in Cell-Free MIMO Systems

Cell-free (CF) massive multiple-input multiple-output (MIMO) systems are expected to provide high spectral efficiency to all users, regardless of their locations, when equipped with a large number of evenly distributed access points (APs) in the area of coverage. In this paper, we investigate beamforming and power allocation schemes in CF MIMO systems to achieve user fairness, while maintaining high spectral efficiency without degrading the performance of users with good channel conditions, even as the number of users scales up. The system models and optimization problems for both downlink and uplink are described in a unified mathematical framework. For achieving user fairness, three different approaches are used, i.e., maximizing the minimum received signal power, minimizing the maximum interference power, and maximizing the minimum of signal to interference and noise ratio (SINR). By decoupling beamforming and power allocation problems, the beamforming problems can be formulated as the generalized eigenvalue problems, and the optimal solutions correspond to well-known schemes such as maximum ratio, zero-forcing, and minimum mean square error combining/transmission. In addition to beamforming, we provide closed-form solutions for optimal power allocation by incorporating additional objectives such as minimum total transmit power or evenly balanced SINR when needed. Our performance comparison suggests that to achieve evenly high data rates for all users irrespective of their locations or the number of users, active interference suppression is necessary instead of relying on maximum ratio combining/transmission even with many APs employed.
Predictive maintenance of wind turbine’s main bearing using wind farm SCADA data and LSTM neural networks

Field failures of wind turbine main bearings cause unwanted downtime and significant maintenance costs. Currently, this industry seeks to increase its reliability, for which condition monitoring and predictive maintenance systems have been adopted. In most industrial wind farms, the integrated Supervisory Control and Data Acquisition (SCADA) system provides data that is stored averaged every 10 minutes that can be used to quantify the health of a wind turbine (WT). This research presents a framework for the analysis of data collected from the SCADA system of an operating wind farm, aiming to early detect the main bearing failure using a Long-Short-Term Memory (LSTM) neural network. For prediction, SCADA variables of the temperature of turbine components near the main bearing, rotor speed, ambient temperature, and generated power are taken into account. The results show that the proposed methodology can detect the target failure up to 4 months in advance of the fatal breakdown. The results obtained confirm the applicability of the proposed model in real scenarios that can help the operator with enough time to make more informed maintenance decisions.
A multi-segment multi-pulse maneuver control method for micro satellite

Aiming at the constraint due to micro satellite orbital maneuverability and relative navigation, a multi-segment multi-pulse maneuver control method is proposed for approaching a target satellite. Convert the along-track approaching trajectory into an impulsive control problem with fixed time and fixed distance. With time and distance from origin to destination as the optimization objectives, the time-distance optimal solution set is generated under the delta-v constraint and trajectory constraint. The planning function is obtained by fitting a segmented polynomial to the optimal solution set. In the approach mission, the maneuver time to reach the expected terminal is determined based on the planning function, and the approaching to the terminal is accomplished using fixed-time multi-pulse control. Based on the simulation scenario, a multi-segment maneuvering strategy is obtained according to the optimization result, and the mission simulation is completed using the three-pulse control. The results show that the proposed multi-segment multi-pulse maneuver control method can reliably complete the approach mission under the constraints.
Parameter modelling of fleet gas turbine engines using gated recurrent neural networks

Oriented by the gas-path fault diagnosis of aircraft engines, this work presents a novel parameter modelling scheme for fleet gas turbine engines based on gated recurrent neural networks. Four dynamic models are constructed based on the long short-term memory (LSTM) network and gated recurrent unit (GRU) network to predict the total temperature at the high-pressure turbine outlet of gas turbine engines. We apply the dynamic networks to model the engine parameters by solving a sequence-to-feature regression problem. The proposed scheme is assessed through a comprehensive comparison study on training performance, validation performance, generalization, robustness against noise, and extrapolation performance. The results showed that the proposed network models performed a promising performance on parameter modelling. For the proposed four network models, the NARX-based models have better one-step-ahead prediction performance, while the state-space-based models have better long-term prediction performance. The discussion of the results also showed that the GRU network was an effective data-driven model for parameter modelling of gas turbine engines.
The policy plan of ecotourism development of Sakjan Lake for economic empowerment of buffering rural community in the Meru Betiri National Park Jember Indonesia

Meru Betiri National Park is a conservation area for the biodiversity of flora and fauna. In the implementation, conservation activities should provide economic benefits for the buffer community to build participation in conservation activities. This study aims to find out a policy plan for developing the ecotourism destination of Sakjan Lake in Meru Betiri National Park Jember. The analysis uses the Tinbergen Rule with consideration of endogenous and exogenous variables in achieving the final goal of community empowerment of buffer villages without neglecting the nature conservation in the Meru Betiri National Park. The results show that policy plans consist of zoning changes to the location of Sakjan Lake, maximum protection of natural preservation, tourist safety, community empowerment with a participatory approach, keeping off ecotourism paradoxes and determining a proper strategy for ecotourism development. Ecotourism activities of Sakjan Lake should be directed to the economic improvement of the local community without breaking the regulation related to the existence of Meru Betiri National Park and safety attention for visitors, so that ecotourism activities are not only for income generating but also for nature and environmental conservation.