Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuroevolution-based Classifiers for Deforestation Detection in Tropical Forests

Tropical forests represent the home of many species on the planet for flora and fauna, retaining billions of tons of carbon footprint, promoting clouds and rain formation, implying a crucial role in the global ecosystem, besides representing the home to countless indigenous peoples. Unfortunately, millions of hectares of tropical forests are lost every year due to deforestation or degradation. To mitigate that fact, monitoring and deforestation detection programs are in use, in addition to public policies for the prevention and punishment of criminals. These monitoring/detection programs generally use remote sensing images, image processing techniques, machine learning methods, and expert photointerpretation to analyze, identify and quantify possible changes in forest cover. Several projects have proposed different computational approaches, tools, and models to efficiently identify recent deforestation areas, improving deforestation monitoring programs in tropical forests. In this sense, this paper proposes the use of pattern classifiers based on neuroevolution technique (NEAT) in tropical forest deforestation detection tasks. Furthermore, a novel framework called e-NEAT has been created and achieved classification results above 90% for balanced accuracy measure in the target application using an extremely reduced and limited training set for learning the classification models. These results represent a relative gain of 6.2% over the best baseline ensemble method compared in this paper
Simpler and Better Cardinality Estimators for HyperLogLog and PCSA

Cardinality Estimation (aka Distinct Elements ) is a classic problem in sketching with many industrial applications. Although sketching algorithms are fairly simple, analyzing the cardinality estimators is notoriously diﬃcult, and even today the state-of-the-art sketches such as HyperLogLog and (compressed) PCSA are not covered in graduate level Big Data courses. In this paper we deﬁne a class of generalized remaining area ( τ -GRA ) estimators, and observe that HyperLogLog , LogLog , and some estimators for PCSA are merely instantiations of τ -GRA for various integral values of τ . We then analyze the limiting relative variance of τ -GRA estimators. It turns out that the standard estimators for HyperLogLog and PCSA can be improved by choosing a fractional value of τ . The resulting estimators come very close to the Cram´er-Rao lower bounds for HyperLogLog and PCSA derived from their Fisher information. Although the Cram´er-Rao lower bound can be achieved with the Maximum Likelihood Estimator (MLE), the MLE is cumbersome to compute and dynamically update. In contrast, τ -GRA estimators are trivial to update in constant time. Our presentation assumes only basic calculus and probability, not any complex analysis [FM85, DF03, FFGM07].
Spatially resolved gas and stellar kinematics in compact starburst galaxies

The kinematics of galaxies provide valuable insights in their physics and assembly history. Kinematics are governed not only by the gravitational potential, but also by merger events and stellar feedback processes such as stellar winds and supernova explosions. Aims. We aim at identifying what governs the kinematics in a sample of SDSS selected nearby starburst galaxies, by obtaining spatially resolved measurements of the gas and stellar kinematics. We obtain near-infrared integral field K-band spectroscopy with VLT/SINFONI of 15 compact starburst galaxies. We derive the integrated as well as spatially resolved stellar and gas kinematics. The stellar kinematics are derived from the CO absorption bands, and Pa$\alpha$ and Br$\gamma$ emission lines are used for the gas kinematics. Based on the integrated spectra we find that the majority of galaxies have gas and stellar velocity dispersion that are comparable. A spatially resolved comparison shows that the six galaxies that deviate show evidence for a bulge or stellar feedback. Two galaxies are identified as mergers based on their double peaked emission lines. In our sample, we find a negative correlation between the ratio of the rotational velocity over the velocity dispersion (vrot/$\sigma$) and the star formation rate surface density. We propose a scenario where the global kinematics of the galaxies are determined by gravitational instabilities that affect both the stars and gas. This process could be driven by mergers or accretion events. Effects of stellar feedback on the ionised gas are more localised and detected only in the spatially resolved analysis. The mass derived from the velocity dispersion provides a reliable mass even if the galaxy cannot be spatially resolved. The technique used in this paper is applicable to galaxies at low and high redshift with the next generation of infrared focussed telescopes (JWST, ELT).
PU-MFA: Point Cloud Up-Sampling via Multi-Scale Features Attention

Recently, research using point clouds has been increasing with the development of 3D scanner technology. According to this trend, the demand for high-quality point clouds is increasing, but there is still a problem with the high cost of obtaining high-quality point clouds. Therefore, with the recent remarkable development of deep learning, point cloud up-sampling research, which uses deep learning to generate high-quality point clouds from low-quality point clouds, is one of the fields attracting considerable attention. This paper proposes a new point cloud up-sampling method called Point cloud Up-sampling via Multi-scale Features Attention (PU-MFA). Inspired by prior studies that reported good performance at generating high-quality dense point set using the multi-scale features or attention mechanisms, PU-MFA merges the two through a U-Net structure. In addition, PU-MFA adaptively uses multi-scale features to refine the global features effectively. The PU-MFA was compared with other state-of-the-art methods in various evaluation metrics through various experiments using the PU-GAN dataset, which is a synthetic point cloud dataset, and the KITTI dataset, which is the real-scanned point cloud dataset. In various experimental results, PU-MFA showed superior performance of generating high-quality dense point set in quantitative and qualitative evaluation compared to other state-of-the-art methods, proving the effectiveness of the proposed method. The attention map of PU-MFA was also visualized to show the effect of multi-scale features.
FedMCSA: Personalized Federated Learning via Model Components Self-Attention

Federated learning (FL) facilitates multiple clients to jointly train a machine learning model without sharing their private data. However, Non-IID data of clients presents a tough challenge for FL. Existing personalized FL approaches rely heavily on the default treatment of one complete model as a basic unit and ignore the significance of different layers on Non-IID data of clients. In this work, we propose a new framework, federated model components self-attention (FedMCSA), to handle Non-IID data in FL, which employs model components self-attention mechanism to granularly promote cooperation between different clients. This mechanism facilitates collaboration between similar model components while reducing interference between model components with large differences. We conduct extensive experiments to demonstrate that FedMCSA outperforms the previous methods on four benchmark datasets. Furthermore, we empirically show the effectiveness of the model components self-attention mechanism, which is complementary to existing personalized FL and can significantly improve the performance of FL.
Variable Dynamic Mode Decomposition for Estimating Time Eigenvalues in Nuclear Systems

Abstract We present a new approach to calculating time eigenvalues of the neutron transport operator (also known as eigenvalues) by extending the dynamic mode decomposition (DMD) to allow for nonuniform time steps. The new method, called variable dynamic mode decomposition (VDMD), is shown to be accurate when computing eigenvalues for systems that were infeasible with DMD due to a large separation in timescales (such as those that occur in delayed supercritical systems). The eigenvalues of an infinite medium neutron transport problem with delayed neutrons, and consequently having multiple, very different relevant timescales, are computed. Furthermore, VDMD is shown to be of similar accuracy to the original DMD approach when computing eigenvalues in other systems where the previously studied DMD approach can be used.
L-theory of $C^*$-algebras

We establish a formula for the L-theory spectrum of real C ∗ -algebras from which we deduce a presentation of the L-groups in terms of the topological K-groups, extending all previously known results of this kind. Along the way, we extend the integral comparison map τ : k → L obtained in previous work by the ﬁrst two authors to real C ∗ -algebras and interpret it using topological Grothendieck–Witt theory. Finally, we use our results to give an integral comparison between the Baum–Connes conjecture and the L-theoretic Farrell–Jones conjecture, and discuss our comparison map τ in terms of the signature operator on oriented manifolds.
On the clique number of noisy random geometric graphs

Let Gn$$ {G}_n $$ be a random geometric graph, and then for q,p∈[0,1)$$ q,p\in \left[0,1\right) $$ we construct a (q,p)$$ \left(q,p\right) $$ ‐perturbed noisy random geometric graph Gnq,p$$ {G}_n^{q,p} $$ where each existing edge in Gn$$ {G}_n $$ is removed with probability q$$ q $$ , while and each non‐existent edge in Gn$$ {G}_n $$ is inserted with probability p$$ p $$ . We give asymptotically tight bounds on the clique number ωGnq,p$$ \omega \left({G}_n^{q,p}\right) $$ for several regimes of parameter.
Virtual ALMA Tour in VRChat: A Whole New Experience

Many forefront observatories are located in remote areas and are difficult to visit, and the global pandemic made visits even harder. Several virtual tours have been executed on YouTube or Facebook Live, however, it is difficult to feel a sense of immersion and these are far from the actual experience of visiting a site. To solve this problem, we pursued an astronomy outreach event on the virtual reality social platform VRChat. To provide an experience similar to visiting the site, we performed a virtual tour of the ALMA Observatory in VRChat guided by an ALMA staff member. 47 guests participated in the tour. The post-event survey showed that the overall lecture and guided tour were very positively accepted by the participants. Respondents answered that the communication in the VRChat was more intensive than in other online outreach events or on-site public talks. The ratio of respondents who answered that they were able to communicate well with the guide was higher for those who used head mounted displays than for those who participated in other ways. 40 answered that the tour increased their interest in astronomy, and this did not show a clear difference depending on how they participated. In the free descriptions in the responses, there were noticeable mentions of the physical sensations received from the realistic 3D space, which left a positive and strong impression on the participants. The responses show that VRChat has the potential to be a strong tool for astronomy communication in the pandemic and post-pandemic eras .
Time-Division Multiplexing Light Field Display With Learned Coded Aperture

Conventional stereoscopic displays suffer from vergence-accommodation conflict and cause visual fatigue. Integral-imaging-based displays resolve the problem by directly projecting the sub-aperture views of a light field into the eyes using a microlens array or a similar structure. However, such displays have an inherent trade-off between angular and spatial resolutions. In this paper, we propose a novel coded time-division multiplexing technique that projects encoded sub-aperture views to the eyes of a viewer with correct cues for vergence-accommodation reflex. Given sparse light field sub-aperture views, our pipeline can provide a perception of high-resolution refocused images with minimal aliasing by jointly optimizing the sub-aperture views for display and the coded aperture pattern. This is achieved via deep learning in an end-to-end fashion by simulating light transport and image formation with Fourier optics. To our knowledge, this work is among the first that optimize the light field display pipeline with deep learning. We verify our idea with objective image quality metrics (PSNR, SSIM, and LPIPS) and perform an extensive study on various customizable design variables in our display pipeline. Experimental results show that light fields displayed using the proposed technique indeed have higher quality than that of baseline display designs.
Metal‐frame‐integrated eight‐element multiple‐input multiple‐output antenna array in the long term evolution bands 41/42/43 for fifth generation smartphones

A metal‐frame‐integrated eight‐antenna array operating in the long term evolution bands 41/42/43 (2.496 GHz‐2.69 GHz, 3.4 GHz‐3.8 GHz) for future fifth generation multiple‐input multiple‐output (MIMO) applications in smartphones is presented and discussed. The proposed eight‐antenna MIMO array is formed by integrating four identical building blocks, each of which consists two dual‐mode monopole antenna elements with a neutralization line (NL) embedded in between. Part of the metal frame is exploited to increase the effective resonant length of the monopole antenna. By using the wideband NL, two transmission dips can be generated, and thus an improved isolation (>10 dB) is achieved. The proposed antenna array was simulated and experimentally tested. Good antenna efficiency (>44%) and low envelope correlation coefficient (<0.2) were obtained in the bands of interest. In an 8 × 8 MIMO system with 20 dB signal‐to‐noise ratio, the calculated ergodic channel capacity was as high as 38 bps/Hz in the low band, and 38.3 bps/Hz in the high band. Details of the proposed antenna array are described. The simulated, measured, and calculated results are presented.
A Non-Hermitian two coupled Sachdev-Ye-Kitaev model

We propose a non-Hermitian two coupled Sachdev-Ye-Kitaev model, but its thermodynamic structure is similar to Hermitian two coupled SYK model. The non-Hermiticity greatly modiﬁes the properties of the ground states and the oﬀ-diagonal Green’s functions. Supersingly, the energy spectrum, the degree of entanglement of the ground states of the two SYK are not inﬂuenced by the non-Hermiticity. Meanwhile, the free energy as a function of temperature shows ﬁrst order phase transition between gapped and gapless phases independent of the non-Hermicity.
A review on attraction factors of science and technology parks to firms in health sector

BACKGROUND: Over the past few years, a rapidly growing number of science and technology parks (STPs) in health sector have emerged across the world. There has been little discussion in the literature to show how STPs could make an attractive environment to absorb and retain potential firms. This is even more challenging for specialized STPs in health sector. The aim of this study is to identify the attractive factors for firms in a STP in health sector. MATERIALS AND METHODS: A scoping review method was undertaken to review the literature on seven databases (ScienceDirect, Scopus, ProQuest, Google Scholar, EconPapers, PubMed, and ISI Web of Science) for peer-reviewed articles published until 2019. The search results were screened against the inclusion of criteria to ensure they met the objectives. The eligible papers were then assessed on the basis of the full text, and finally the results were extracted. RESULTS: The attractive factors for firms and talents in multidimensional STPs and those in health sector are extracted and summarized. The attractive factors of multidimensional STPs, which includes health sector firms, and those specialized in health sector are summarized in three main categories; factors created by government and universities, and factors related to STP policies and those expected by the firms. CONCLUSION: To make STPs attractive for firms in health sector, there is a list of factors that are required to be done not only by STP itself, but also by the national and local government and industries. It is important to consider the factors that are expected by the firms to be implemented. The results of this study suggest that making STPs attractive for health sector firms needs close collaboration between government, universities, related industries, and STPs all together.
Evaluating the usability of a national health information system with heuristic method

BACKGROUND: Hospital Statistics and Information System is one of the most important health information systems in Iran used in all hospitals in this country. Usability problems can reduce the speed and precision of users when interacting with this system. This study aimed to identify the usability problems of a national health system called “AVAB”. MATERIALS AND METHODS: This descriptive cross-sectional study was conducted in 2020, and three experts evaluated the usability of this system independently by the heuristic evaluation method. Nielsen's usability principles were used to identify usability problems and to classify their severity. RESULTS: A total of 86 unique problems were identified. The highest number of problems were related to the two principles of “help and documentation” and “match between system and the real world” with 23 and 11 usability problems, respectively. The lowest number of problems were related to the two principles of “visibility of system status” and “help users recognize, diagnose, and recover from errors,” each with three problems. 58.1% of the identified problems were in the group of major and catastrophic problems. CONCLUSIONS: With the help of heuristic evaluation method, a significant number of usability problems of Hospital Statistics and Information System were identified. Most of the identified problems were major and catastrophic, and it is necessary to solve these problems by the designers and developers of this system.
Challenges and opportunities in the implementation of competency-based medical education – A cross-sectional survey among medical faculty in India

BACKGROUND: In India, competency-based medical education (CBME) is gaining foothold to transform the medical student into a doctor fulfilling community and societal needs. With that end in view the teaching faculty are getting sensitized and trained by the National Faculty Development Program (FDP). We aimed to assess the awareness about FDP among teaching faculty in medical colleges and study the attitude and perceived barriers to implementation of CBME. METHODOLOGY: A cross-sectional, electronically distributed, questionnaire-based study was conducted among medical faculty in India. The questionnaire identified participants’ awareness, attitude, and perceived barriers to CBME. Descriptive analysis was employed for continuous variables and internal comparison employing Chi-square test with α <0.05 for statistical significance. RESULTS: Among 251 participants 90.2% faculties from private institutes had undergone FDP as against 71% from Government sector (P = 0.008). We observed that 92.4% were aware, 80.2% had undergone Curriculum Implementation Support Program and 95.2% did agree that CBME will improve the medical education system. Major challenges perceived were high student to faculty ratio (67.7%), ill developed infrastructure (41.4%) and difficulties in assessment (41.1%). The popular solutions suggested were to increase faculty strength (73.7%), improve infrastructure (69.3%), extra remuneration (35.9%) and increase administrative support (30.7%). There was significant difference of opinions between teaching faculty of government and private sector (P = 0.017). CONCLUSION: Most of the medical faculty are aware of the need and have acquired a positive attitude towards enforcement of CBME. However, significant barriers do exist in the form of manpower and resources which need to be addressed.
Impact of online education due to the pandemic among college students: Knowledge, Attitude and Practices analysis with structural equation modeling

Pandemic 2019 is observed in all sectors of the world which had caused a huge disruption in the education system in India as well as worldwide adding challenges to student's life. We aimed to provide an outline on E-Learning and the difficulties experienced by students of various colleges in the southern parts of India and to conduct knowledge, attitude and practices (KAP) analysis based on student's perception regarding E-learning by collecting an online survey, 346 valid questionnaires were retrieved. In order to evaluate the association between the variables of KAP, structural equation modeling was used for data analysis. The influencing factors of KAP were observed to know the effect of the pandemic on E-learning from the model. The result finding moderately fit the collected data and reveals a good fit of the model in the means of satisfying the threshold values.
Multiple location experiment of technique system for direct rational application of vinasse from cane mill in sugarcane fields.

For purposes of eliminating environmental pollution and transferring the waste into valuable fertilizer through rationally applying it in sugarcane fields directly,a technique system for direct rational application of vinasse from cane mill in sugarcane fields was established,and different rates of fresh vinasse were experimented in 6 sides of different regions representing different ecological conditions in Guangxi,China in 2005.Based on the performance of both the plant and ratoon crops,the average cane tonnages were 92.3,102.5 and 93.7 t/hm2 for the treatments with 45,75 and 105 t/hm2 vinasse,respectively,which were 13.24 %,17.55 % and 14.92 % higher than that of non-fertilizing control(CK1),and 7.66 %,11.75 % and 9.25 % higher than that of the conventional fertilization control(CK2),respectively.The sucrose % cane was 14.66 %,14.85 % and 14.83 %,for the treatments with 45,75 and 105 t/hm2 vinasse,respectively,which was 0.06 %,0.25 % and 0.23 % higher than that of CK1,and 0.11 %,0.30 % and 0.28 % higher than that of CK2,respectively.The above experimental results showed that the vinasse from sugarcane mill should be a very good complete organic fertilizer for sugarcane,and the fresh vinasse could be rationally applied in the fields without any dilution or pretreatment,which would produce significant increases in cane tonnage and sucrose % cane and reducing the chemical fertilizer application and production cost so resulting in more profit for sugarcane and sugar production while avoiding environmental pollution,and especially,the treatment with 75 vinasse showed the best economic benefit.The direct rational application of fresh vinasse in sugarcane fields is practically possible through a set of technical measures.
How using the Revenues of the German HGV motorway system efficiently and equitable under different regulatory frameworks and institutional settings

Topic: Regulation / Public Private Partnerships in road infrastructure management Authors: Dr. Claus Doll, Tel. : +49 721 6809-354, Fax: +49 721 6809-135, Email: claus.doll@isi.fraunhofer. de Dr. Wolfgang Schade, Tel. : +49 721 6809-353, Fax: +49 721 6809-135, Email: wolfgang.schade@isi.fraunhofer. de Fraunhofer-Institute for Systems and Innovation Research (ISI) Breslauer Str. 48, D-76139 Karlsruhe, Germany Date: 23.9. 2005