Miracle-dz/UniFAR-FTUs huggingface dataset:
Fish-bone subwavelength grating waveguide photonic integrated circuit sensor array

Recent advances in subwavelength grating (SWG) structures have shown promise in sensing applications. Though prior sensors have obtained high index sensitivities, their designs have not focused on providing strong analyte/light interaction efficiency for low analyte concentration flows. We have explored high-contrast grating “fish-bone” and segmented SWG structures in the hopes of improving this aspect. We present below the progress of our design exploration of these structures and compare their performance to a typical slot waveguide to understand their impact on spectral transmission and analyte interaction. The best performing structures will be experimentally functionalized with label-free analyte capture materials to sense specific threat molecules via index change. We envision building manyanalyte multiplexed sensor arrays from these devices to enable simultaneous monitoring of multiple chemical and biological threats or human biomarkers with high sensitivity, specificity, and low probabilities of false alarm.
Nonlinear Set-based Model Predictive Control for Exploration: Application to Environmental Missions

: Acquiring vast and reliable data of physicochemical parameters is critical to environment monitoring. In the context of water quality analysis, data collection solutions have to overcome challenges related to the scale of environments to be explored. Sites to monitor can be large or remote. These challenges can be approached by the use of Unmanned Vehicles (UVs). Robots provide both ﬂexibility on intervention plans and technological methods for real-time data acquisition. Being autonomous, UVs can explore areas difﬁcult to access or far from the shore. This paper presents a nonlinear Model Predictive Control (MPC) for UV-based exploration. The strategy aims to improve the data collection of physicochemical parameters with the use of an Unmanned Surface Vehicle (USV) targeting water quality analysis. We have performed simulations based on real ﬁeld experiments with a SPYBOAT® on the Heron Lake in Villeneuve d’Ascq, France. Numerical results suggest that the proposed strategy outperforms the schedule of mission planning and exploration for large areas.
Driving Robotic Leg by Lightweight, Low Friction, High Power Hydraulic Actuator for Tough Robots

Article / Book Information 論題 タフロボット用軽量・低摺動・大出力油圧アクチュエータによるロボ ット脚の駆動 Title Driving Robotic Leg by Lightweight, Low Friction, High Power Hydraulic Actuator for Tough Robots 著者 辺見森象, 廣田善晴, 難波江裕之, 遠藤玄, 鈴森康一 Author Morizo Hemmi, Yoshiharu Hirota, Hiroyuki Nabae, Gen Endo, Koichi Suzumori 掲載誌/書名 ロボティクス・メカトロニクス講演会2017講演論文集, Vol. , No. , pp. Journal/Book name Proceedings of the 2017 JSME Conference on Robotics and Mechatronics, Vol. , No. , pp. 発行日 / Issue date 2017, 5 URL http://www.jsme. or.jp/publish/transact/index.html
Exploiting properties of the human auditory system and compressive sensing methods to increase noise robustness in ASR

Human speech comprehension is much more resilient against background noise than the most powerful automatic speech recognizers. That is due in no small part to the fact that conventional systems discard potentially relevant information upfront: the analysis of the audio signals. This is because classical theories do not know how to harness this information. We tried to develop techniques that approximate the way in which the human auditory system analyzes speech, and the way in which the brain processes the analysis results. as closely as possible. The results of the project are positive and not so positive. In the presence of loud background noise our approach is superior; it makes fewer errors, and the errors are more similar to human errors. In the absence of background noise our approach is somewhat less accurate, for reasons that we do not yet fully understand. However, the blame surely is not with our way of analyzing acoustic signals.
Privacy concerns in smart cities

textabstractIn this paper a framework is constructed to hypothesize if and how smart city technologies and urban big data produce privacy concerns among the people in these cities (as inhabitants, workers, visitors, and otherwise). The framework is built on the basis of two recurring dimensions in research about people's concerns about privacy: one dimensions represents that people perceive particular data as more personal and sensitive than others, the other dimension represents that people's privacy concerns differ according to the purpose for which data is collected, with the contrast between service and surveillance purposes most paramount. These two dimensions produce a 2 × 2 framework that hypothesizes which technologies and data-applications in smart cities are likely to raise people's privacy concerns, distinguishing between raising hardly any concern (impersonal data, service purpose), to raising controversy (personal data, surveillance purpose). Specific examples from the city of Rotterdam are used to further explore and illustrate the academic and practical usefulness of the framework. It is argued that the general hypothesis of the framework offers clear directions for further empirical research and theory building about privacy concerns in smart cities, and that it provides a sensitizing instrument for local governments to identify the absence, presence, or emergence of privacy concerns among their citizens.
A Modified Polynomial Preserving Recovery Technique

: In this work, the polynomial preserving recovery method is enhanced by increasing the order of the ﬁtting polynomial within the same patch. This is achieved by adding more sample points inside the elements of the patch then substitute them in the discretized form of the differential equation. These sample points are the set of superconvergent points of the patch under consideration. Numerical results show that the recovered gradient at the nodes with linear elements is superconvergent. The proposed method improves the accuracy of the recovered gradient over the domain of the solution with the same rate of convergence of the polynomial preserving recovery technique.
Using Artificial Neural Networks to Perform Feature Selection on Microarray Data

—This article illustrates a feature selection technique that makes use of artificial neural networks. The problem being faced is the analysis of microarray expression data, which requires a mandatory feature selection step due to the strong imbalance between number of features and size of the training set. The proposed technique has been assessed on relevant benchmark datasets. All datasets report gene expression levels taken from female subjects suffering from breast cancer against normal subjects. Experimental results, with average accuracy of about 84% and very good balance between specificity and sensitivity, point to the validity of the approach.
Burden and Cost of Anterior Cruciate Ligament Reconstruction and Reimbursement of Its Treatment in a Developing Country: An Observational Study in Indonesia

Objective The number of anterior cruciate ligament reconstruction (ACLR) procedures is increasing. However, ACLR procedures are likely to be underbudgeted in a developing country like Indonesia. This study aimed to analyze costs for ACLR procedures in Indonesia’s resource-limited context, determine the burden of ACLR, and suggest national prices for ACLR reimbursement. Methods A retrospective observational study was conducted between 1 January and 31 December 2019 on the cost of ACLR from a payer perspective using inpatient billing records in four hospitals. The national burden of ACLR was calculated, and projected national prices for reimbursement were determined. Results Of 80 ACLRs, 53 (66%) were isolated ACLRs and 27 (34%) ACLRs were combined with meniscus treatment. Mean hospital costs incurred per ACLR procedure were US$ 2853, with the dominant cost relating to orthopedic implant prices (US$ 1,387.80). The costs of ACLR with combined meniscus treatment were estimated as being 35% higher than isolated ACLR. The national burden of ACLR showed a total budget of US$ 367.4 million per 100,000 patients (0.03% of GDP) for ACLR with additional meniscus treatment and US$ 271.3 million per 100,000 patients (0.02% of GDP) for isolated ACLR. Conclusion ACLR procedures in Indonesia are likely underbudgeted. Adjustments of reimbursement prices for ACLR are needed to facilitate adequate access of Indonesians to the procedures. This study demonstrated varying costs determined for ACLR in Indonesia, which entails that a new reimbursement system with improvement of national prices should become the core of transformation.
Institutional Partnerships for Transfer Student Success: An Examination of Catalysts and Barriers to Collaboration

Objective: Strong institutional partnerships are critical to the transfer process for students because they can help ease navigation from one college to the next. This research seeks to better understand the nature of high-performing transfer partnerships, and the factors that can either promote or hinder their development. Methods: Drawing upon qualitative data from a larger mixed methods study, we visited seven institutional pairs of community college (sending) and baccalaureate-granting (receiving) institutions and interviewed 170 administrators, staff, and faculty. Data were analyzed using perspectives on educational collaborations and the forces that can impact organizational change efforts. Results: Our findings highlight factors that influence the development, growth, or continuation of transfer partnerships. We propose a framework that can be used to analyze transfer partnerships based on institutional culture, practices, and policies. Contributions: This research extends the work on transfer partnerships by providing a comprehensive picture of the organizational forces that impact their change over time. We also offer suggestions for how these findings can be used to develop or enhance transfer partnerships that can move institutions toward more equitable student outcomes.
Karakteristik Penyebaran Panas Menggunakan Metode Termografi Pada Pompa Sentrifugal Tigkat Tunggal

Abstrak: Pompa sentrifugal di industri merupakan mesin yang memiliki tingkat kritis tinggi, maka perlu dilakukan penerapan pemeliharaan prediktif disamping pemeliharaan berkala agar kerusakan dapat diketahui sedini mungkin dan kerusakan lebih jauh dapat dicegah. Salah satu teknik pemeliharaan prediktif yang dapat diterapkan adalah inspeksi penyebaran panas atau termografi. Namun, Penerapan termografi untuk keperluan monitoring kondisi mesin khususnya untuk pompa sentrifugal tingkat tunggal masih kurang, sehingga diperlukan kajian lebih lanjut. Pengujian termografi ini dilakukan pada pompa sentrifugal dengan beban tetap yaitu katup tekan terbuka penuh dan lama operasi pada instalasi sirkulasi tertutup. Percobaan dilakukan selama 120 menit dengan pemindaian pertama dilakukan pada waktu operasi 30 menit, selanjutnya pemindaian dilakukan pada operasi 45 menit, 60 menit, 75 menit, 90 menit, 105 menit, dan terakhir 120 menit. Titik titik pemindaiannya yaitu Motor Body (MB), Bearing Motor Drive End (BMDE), Coupling (CPL), Bearing Pump (BPUM), Shaft of Pump (SPUM) dan Pump Body (PB). Hasil dari pengujian termografi menunjukkan bahwa kenaikan temperatur secara umum naik secara signifikan. Kenaikan temperatur tertinggi paling cepat terjadi pada bagian Pump Body (PB). Panas tertinggi mencapai 52,4°C, dengan perubahan panas dari 36,8°C sampai 52,4°C dalam interval waktu 30-120 menit. Kata kunci: Pemeliharaan prediktif, termografi, penyebaran panas, pemindaian
Anterior Pituitary Hormones in Blood and Cerebrospinal Fluid of Patients in Neurocritical Care

Background: Anterior pituitary hormones in blood follow a circadian rhythm, which may be influenced by various factors such as intracranial pathologies. In cerebrospinal fluid (CSF), pituitary hormones have been collected only selectively and circadian rhythm has not yet been investigated. This pilot study analysed diurnal variations of anterior pituitary hormones in patients in neurocritical care to determine whether circadian rhythmicity exists in these patients. Possible influences of intracranial pathologies were also investigated. Blood and CSF concentrations were assessed simultaneously to explore the value of blood concentrations as a surrogate parameter for CSF levels. Methods: Blood and CSF samples of 20 non-sedated patients were collected at 06:00, noon, 18:00 and midnight, and analysed for adrenocorticotropic hormone (ACTH), cortisol, thyroid-stimulating hormone (TSH) and insulin-like growth factor-1 (IGF-1) concentrations at each of the four time points. ACTH and IGF-1 were measured by sandwich chemiluminescence immunoassay. Cortisol and TSH were measured by electrochemiluminescence immunoassay. Results: Results showed inconsistent circadian rhythms. Less than 50% of the patients showed a circadian rhythmicity of ACTH, cortisol, TSH or IGF-1. Significance of diurnal variations was only present for blood concentrations of TSH. Correlations between blood and CSF concentrations were strong for cortisol and TSH. Conclusions: CSF concentrations were only in the measurable range in some of the patients. No clear circadian rhythmicity could be identified, except for TSH in blood. Absence of significant diurnal variations could be explained by the underlying pathologies or disturbing influences of the intensive care unit. Blood concentrations of cortisol and TSH may be suitable surrogate parameters for CSF.
Physical Modelling of Advanced SiGeTransistors

Many demanding high speed applications like optical communication operating at 40100 Gb/s and 77 GHz automotive radar require transistors with a cutoff frequency fT of 200 GHz or above. Additionally, these applications also need transistors with high breakdown voltages, which are used e.g. for ESD protection and driver stages. Furthermore, 77 GHz automotive radar applications require varactors with sufficiently high tuning range to be integrated on the same chip. Such an integration of high voltage transistors and varactors with high tuning range into high frequency SiGe bipolar technologies is challenging due to the requirement of a shallow collector for the high speed transistor. In this work, a novel concept with two epitaxial layers is proposed for the simultaneous integration of high speed transistors, high voltage transistors, and varactors with high tuning range on the same chip. Using this concept, high speed transistors with 209 GHz cut-off frequency have been combined with high voltage transistors providing an emitter-collector breakdown voltage of 5 V. Additionally, the same concept allowed the development and optimization of a varactor for a voltage controlled oscillator (VCO) with high tuning range of 13 GHz and sufficiently low phase noise suitable for 77 GHz automotive radar applications. Process and device simulations leading to the optimum device combination, and design considerations related to the process flow, are presented. This work also describes extensive investigations of the emitter, collector, and base for improving the speed of future high speed transistors. As a part of emitter optimization, it has been found that by using a relatively simple un-doped silicon cap instead of the conventional p-doped silicon cap the cutoff frequency fT increases by 15 GHz (10 %). This is verified by simulation and experiment. Using the double epi concept, the collector thickness of the high speed transistor can be reduced independent from the requirements of the high voltage transistor. A detailed simulation study concerning the collector thickness and doping for achieving high speed is presented as a part of collector optimization. Investigations show that by using a thin collector of 40 nm and a high collector doping of 1.5 × 10 cm in the standard high speed transistor an improvement in cutoff frequency of 45 GHz can be achieved. As a result of base optimization, it has been found that the combination of lateral emitter scaling down to 80 nm, a thin emitter-base spacer of 30 nm, high doping of 2 × 10 cm in the extrinsic base link region, and extending the base contact towards the emitter increases the maximum oscillation frequency fmax of the high speed transistor up to 700 GHz, which means a doubling of the present performance.
RECORDS OF PHARMACEUTICAL AND BIOMEDICAL SCIENCES Nanocarriers as pulmonary drug delivery systems

The lung is an attractive target for drug delivery due to noninvasive administration via inhalation aerosols, avoidance of first-pass metabolism, direct delivery to the site of action for the treatment of respiratory diseases, and the availability of a huge surface area for local drug action and systemic absorption of drug. Nanocarrier systems in pulmonary drug delivery offer many advantages such as the potential to achieve relatively uniform distribution of drug dose among the alveoli, achievement of improved solubility of the drug from its own aqueous solubility, a sustained drug release which consequently reduces dosing frequency, improves patient compliance, decreases incidence of side effects, and the potential of drug internalization by cells. This review focuses on the different types of the nanocarrier systems used in pulmonary drug delivery with special attention to their pharmaceutical aspects.
Heterogeneous Interactive Snapshot Network for Review-Enhanced Stock Profiling and Recommendation

Stock recommendation plays a critical role in modern quantitative trading. The large volumes of social media information such as investment reviews that delegate emotion-driven factors, together with price technical indicators formulate a “snapshot” of the evolving stock market profile. However, previous studies usually model the temporal trajectories of price and media modalities separately while losing their interrelated influences. Moreover, they mainly extract review semantics via sequential or attentive models, whereas the rich text associated knowledge is largely neglected. In this paper, we propose a novel heterogeneous interactive snapshot network for stock profiling and recommendation. We model investment reviews in each snapshot as a heterogeneous document graph, and develop a flexible hierarchical attentive propagation framework to capture fine-grained proximity features. Further, to learn stock embedding for ranking, we introduce a novel twins-GRU method, which tightly couples the media and price parallel sequences in a cross-interactive fashion to catch dynamic dependencies between successive snapshots. Our approach excels state-of-the-arts over 7.6% in terms of cumulative and risk-adjusted returns in trading simulations on both English and Chinese benchmarks.
Hybrid Approach to Business Software Development in Terms of Current Needs and Requirements

: Business traditional software development methods rely on a work plan to extract complete sets of documentation, architectural, and high-level project development and control requirements. Agile has gained immense popularity in the ﬁeld of computer science in recent years, although it combines acceptable software engineering practices with the controversial ones. The software industry has ﬁnally come to the conclusion that speciﬁc project characteristics such as purpose, scope, requirements, resources, architecture and size determine the methodology that best ﬁts the project realities. The paper presents hybrid approaches, combining the PRINCE2 methodology and the Scrum method, in order to take maximum advantage of the methodologies and minimize their disadvantages by using the strengths of one methodology on the weaknesses of the other.
Improving Car Detection from Aerial Footage with Elevation Information and Markov Random Fields

: Convolutional neural networks are often trained on RGB images because it is standard practice to use transfer learning using a pre-trained model. Satellite and aerial imagery, however, usually have additional bands, such as infrared or elevation channels. Especially when it comes to detection of small objects, like cars, this additional information could provide a signiﬁcant beneﬁt. We developed a semantic segmentation model trained on the combined optical and elevation data. Moreover, a post-processing routine using Markov Random Fields was developed and compared to a sequence of pixel-wise and object-wise ﬁltering steps. The models are evaluated on the Potsdam dataset on the pixel and object-based level, whereby accuracies around 90% were obtained.
The nonlinear relationship between governance structures and Islamic bank stability: Evidence of GCC countries

: The main objective of this paper is to examine the nonlinear relationship between governance structure and the financial stability of Islamic banks in the GCC during the period 2010-2019. The findings of fixed effects regression show that there is an inverted U-shaped non-linear relationship between governance and financial stability, thus indicating aversion banks to insolvency risks and vice versa. This study has significant political implications.
Replacement service decisions for disruption recovery in light rail systems

Purpose Attracting commuters from driving to light rail systems has a good potential for reducing carbon emissions. However, the light rail system is interrupted by disruptions frequently, which reduces its attraction to passengers. Therefore, how to provide a quick replacement service during disruptions is of vital importance to avoid passengers change to other higher emission vehicles. The purpose of this paper is to focus on the decision analysis of the replacement tool for disruption recovery service in urban public light rail systems from the perspective of environmental effect. Design/methodology/approach The traditional approach – bus replacement service – and the new approach – taxi replacement service – which has been recently adopted by several cities, are examined individually and compared. The benefit of the light rail company is formulated by balancing between carbon emission and financial cost. The involving parties’ decision functions taking the passengers’ behaviors as well as numerous other important factors into account are formulated. Findings Both theoretical and numerical sensitivity analyses are conducted to shed light for light rail systems to better coping with disruptions, increasing service level, and attracting more passengers to the environmental transit system to reduce carbon emission. Originality/value It is worth mentioning that this research is a successful application for disruption recovery in a public transit system considering the environmental effect. To the authors’ knowledge, this research is one of the first of such applications in this area and can be used not only in the public light rail systems, but also in other urban public transport network components such as the subway and rail systems.
Comparison of Seismic Design Requirements for Steel Moment Resisting Frames with Emphasis on Stability of Columns in North America, New Zealand, and Europe

The seismic design provisions and stability requirements for steel columns used at the first storey of MRFs as specified is Canadian steel design standard (CSA S16), U.S. design provisions for steel buildings (AISC 341 and AISC 360), the New Zealand steel structures standard (NZS 3404), and Eurocodes 3 and 8 (EC3 and EC8) are reviewed. The code provisions are applied to a deep, slender steel I-shaped column to identify possible failure modes. A finite element analysis of the column is performed under cyclic inelastic lateral drift history to validate code predictions. The column was found to fail by out-of-plane instability, after local buckling has developed in the base plastic hinge. This failure mode was not expected from the axial-bending interaction equations available in the design standards except the equation of Eurocode 3. Limits for out-of-plane slenderness in Canadian and European provisions indicate the observed failure mode.