Miracle-dz/UniFAR-FTUs huggingface dataset:
Single Transverse-Mode Semiconductor Laser Arrays by Parity-Time Symmetry Breaking

Electrically pumped semiconductor laser array operating in the fundamental mode is of vital importance. In general, the competition of multiple transverse modes in the laser array leads to spatiotemporally unstable and degradation of beam quality. In this letter, we propose and experimentally demonstrate electrically pumped single transverse-mode semiconductor laser arrays by exploiting the concept of parity-time symmetry, which is insensitive to fabrication and frequency detuning. Laser arrays composed of four, six and ten-ridge gain lattice have been fabricated, and single transverse-mode operations are observed from the spectral response and far-field radiation. Insensitivity to the fabrication have also been experimentally demonstrated by varying the gap from <inline-formula> <tex-math notation="LaTeX">$1.06 \mu \text{m}$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$1.42 \mu \text{m}$ </tex-math></inline-formula>. The emission power of PT-symmetric laser arrays composed of a four-ridge gain lattice is about five times higher than that of the single-ridge laser with the same current density.
REAL ESTATE MARKET AT A CROSSROAD - ERA OF AFFORDABLE HOUSING IS GONE

Within a broad discussion on property price formation and property market specifics this paper aims to investigate the relationship between property price trends and number of transactions occurred on housing market. Specifically, we test if housing transaction volumes and rents are good predictors of housing prices and discuss causalities and differences in this relationship on the sales and rental property markets. We bring evidence from selected European property markets about the relationship between property price trend and number of transactions occurring on this market. We argue that increased number of transactions is predictive of increase in property price, but prices tend to be rigid in the opposite (downward) direction. Thus, cooling down of demand for properties may rather decrease number of transactions than push down property prices. This appealing result may bring light into understanding why property prices appreciate across time and countries.
Experiment and Simulation Analysis of Multi-layer Glass/Aluminum Anodic Bonding

Abstract Micro-machined multilayered structure plays a significant role as sensing or actuating components in MEMS. Since different thermal expansion parameters and uneven cooling processes in anodic bonding films, it is important to analyze and measure residual stress of the multi-layer glass/aluminum anodic bonding in the cooling process. In this paper, experiments of three-layer, five-layer glass and aluminum anodic bonding samples were made by the public anode method at 400 °C, 600 V and 0.05∼1 MPa for 15 min. Chemical element analysis of the transition layer formed between glass and aluminum during anodic bonding process was analyzed by Energy Dispersive Spectrometry (EDS). Subsequently, residual stresses and strains in cooled three-layer, five-layer and seven-layer anodic bonding samples was analyzed using nonlinear finite element simulation software MARC. Finite element analysis showed that the residual stress and strain distribution in different multi-layer glass and aluminum samples was similar. Simultaneously, finite element analysis indicated that three-layer glass and aluminum anodic bonding samples had smallest residual stress and equivalent strain values in all samples, an important advantage in MEMS fabrication.
Rapid identification of Klebsiella pneumoniae and Serratia marcescens by surface-enhanced Raman spectroscopy

Two types of pathogenic bacteria, Klebsiella pneumoniae and Serratia marcescens, had been reported as important causes of hospital-acquired infection. Rapid and accurate identification of Klebsiella pneumoniae and Serratia marcescens is vitally important for the selection of appropriate treatment modalities. In this article, the feasibility of using surface-enhanced Raman Spectroscopy (SERS) to identify Klebsiella pneumoniae and Serratia marcescens was explored. Spectrum samples were obtained from Klebsiella pneumoniae infections (n=1000) and Serratia marcescens infections (n=1000). The differences between the spectra of two types of pathogenic bacteria were also analyzed. Moreover, Principal Component Analysis- Linear Discriminant Analysis (PCA-LDA) algorithm was used to discriminate the spectra of pathogenic bacteria.
Time Series Based Co-optimization Model of Active and Reactive Power with PV-wind and Storage

With the increasing penetration of renewable energy, the application of distributed power sources is becoming more and more widespread. Distributed generators are involved in the traditional distribution network applications. Energy storage, as a key factor in regulating the voltage load curve, also affects the flow of reactive power and tide through the charging and discharging of electrical energy, and thus plays a critical role in reactive-active co-optimization. This paper propses a time series based co-optimization stratege for energy regulation of distributed power network. Firstly, reactive generators are added and a stage of energy storage siting and capacity setting is carried out. Then active-reactive co-optimization is carried out on this basis, and no energy storage is set as the reference quantity to increase the comparability. Finally, simulation experiment are conducted for a improved system of traditional IEEE33 node. The results show that energy storage has unique advantages in reducing active network loss. And the active-reactive co-optimization has a better performance in reducing network loss and voltage deviation under the state of renewable energy participation.
Determinants of the Quality of Financial Reports

Purpose: This study aims to determine the effect of the internal control system, information technology, applying of accounting standards, human resources competence, and the role of internal auditors on the quality of financial reports of local governments. Theoretical framework: Internal control system, information technology, applying of accounting standards, human resources competence, and the role of internal auditors affect the quality of financial reports. According to the agency theory, the quality of financial reports improves government performance and increasing accountability by reducing the information asymmetry. Additionally, under the agency theory approach, transparency and information are useful in controlling managers and making them responsible for their decisions, as well as overall organizational performance. Design/Methodology: The sample in this study was 126 respondents who were obtained using purposive sampling technique from the financial management and accounting officials of Kendari City, Southeast Sulawesi Province, Indonesia. The analytical method used is multiple linear regression analysis. Findings: The results support the agency theory and found that the internal control system, information technology, applying of accounting standards, and the role of internal auditors had a positive and significant effect on the quality of financial reports of local governments. Meanwhile, human resource competence has a positive but not significant effect on the quality of financial reports of local governments. This shows that the better the internal control system, information technology, applying of accounting standards, and the role of internal audit, the quality of local government financial reports will be better. Research, Practical & Social implications: This study can fill gaps in the results of previous research and helps to provide useful information for local governments in improving the quality of financial reports as an important part of efforts to increase transparency and accountability in the management and reporting of local government finances. Originality/Value: The findings suggest several consequences for the fields of public sector accounting and government governance. Additionally, recent empirical evidence shows that the implementation of accountability in many developing countries, including local government in Indonesia has not yet reached general standards and mainly focuses on compliance with applicable regulations, that this study aids in resolving by examining the factors that determine the quality of local government financial reports.
Aerodynamic Drag Improvements on a Simplified Heavy Vehicle using Three-sided Plain and Notched Base Flaps

An experimental investigation has been undertaken to determine the effects of plain and notched base flaps on the drag performance of simplified tractor-trailer combination without any intermediate gap, Generalized European Transport System (GETS). Both plain and notched base flaps are rigid, made up of three identical flaps whose length is equal to the width of the GETS model, and not angled inward or outward. The experiments examined three-sided flap configurations corresponding to various combinations of seven heights of the plain part (from 10 to 40 mm in steps of 5 mm), four notch amplitudes (from 2.5 to 10 mm in steps of 2.5 mm), and five notch wavelengths (from 10 to 50 mm in steps of 10 mm). It is shown that the drag performance of the plain flap at zero yaw highly depends on the height of the plain flap. The maximum drag reduction occurs for e/w=0.1 yielding a drag reduction of 1.9% when compared to the GETS model without flap (baseline GETS). It was shown that the time-averaged drag coefficient increased slightly until a maximum was reached at e/w=0.3 but then decreased slightly with increasing e/w. Under zero yaw angle conditions, GETS model with a notched base flap, e10-a05.0-λ20, gives the lowest drag. The addition of this base flap to the GETS model resulted in a 2.8% drag reduction. This notched base flap was shown to be more effective not only at reducing under yawed flow conditions tested but also at reducing time-averaged side coefficient under yawed flow conditions tested, compared to the e10-a00.0-λ00 flap.
Application of Deep Transfer Learning in Detection of Lung Cancer: A Systematic Survey

Lung Cancer is the deadliest type of cancer. For diagnosing and detecting lung cancer, many Deep learning techniques are proposed. Deep learning techniques depend on massive data and extracting 3D features of images, which is a tedious task. Therefore deep transfer learning is used as an alternative for better results in medical image analyses like lung cancer, where pre-trained deep learning models are employed, which resolves the problem of labeled data scarcity. As no systematic survey is available in the literature, this paper reviews Lung Cancer detection and diagnosis using Deep Transfer Learning techniques. Moreover, all such methods are compared based on performance parameters like accuracy, Recall, F1- score and precision, etc. The comparison shows that the overall performance of deep learning techniques with the use of Transfer learning is enhanced.
Implant Surface Topography Following Different Laser Treatments: An In Vitro Study

Background Although dental implants have demonstrated very high success rates, they are susceptible to complications such as peri-implantitis that can lead to failure. Methods Twenty implants with surfaces grit-blasted using hydroxyapatite and acid-etched were randomly divided into four groups (five in each group). Three groups were assigned to laser treatments: Group I (erbium, chromium-doped: yttrium, scandium, gallium, and garnet (Er,Cr:YSGG) laser), Group II (650-nm diode laser), and Group III (808-nm diode), and one control group, Group IV. The surface roughness parameters (roughness average(Ra) and root mean square roughness(Rq)) were measured using a non-contact optical profilometer and scanning electron microscope to evaluate the surface topography after the laser treatments. Results Significant differences were observed between the laser groups regarding the surface roughness Ra (3.56±0.26, 3.45±0.19, 3.77±0.42, pc=0.0004, pe=0.0002, pf=0.001) and Rq values (4.49±0.34, 4.35±0.26, 4.72±0.56, pc=0.0007, pe=0.0006, pf=0.002) and the control group (2.81±0.10; 3.57±0.19). However, no significant difference was observed between the different laser treatment modalities. The scanning electron microscope images revealed some morphological changes on the implant surfaces following laser treatment, but no melted morphology was observed. Conclusions The application of Er,Cr:YSGG, 650-nm diode laser, and 808-nm diode did not show melting changes on implant topography. However, some increase in surface roughness was detected. Further studies are recommended to assess the effectiveness of these laser settings on bacterial reduction and osseointegration.
Co‐designing clinical trials alongside youth with chronic pain

Youth have a right to participate in research that will inform the care that they receive. Engagement with children and young people has been shown to improve rates of enrollment and retention in clinical trials as well as reduce research waste. The aim of the study is to gain practical insight on the design of trials specifically on (1) recruitment and retention preferences, (2) potential barriers to research, and (3) study design optimization. Based on this youth engagement, we will co‐design two clinical trials in headaches with youth. Two recruitment strategies were used to recruit 16 youth from across Canada (aged 15–18 years) from an existing youth group, the KidsCan Young Persons' Research Advisory Group (YPRAG) and a new youth group in collaboration with Solutions for Kids in Pain (SKIP). Four virtual, semi‐structured discussion groups were held between April and December 2020, which included pre‐circulated materials and utilized two distinct upcoming planned trials as examples for specific methods feedback. Individual engagement evaluations were completed following the final group session using the Public and Patient Engagement Evaluation Tool. Descriptive results were shared with participants prior to publication to ensure appropriate interpretation. The discussion was centred around three themes: recruitment and retention preferences, potential barriers to participation, and study design optimization. Youth indicated that they would prefer to be contacted for a potential study directly by their physician (not over social media), that they would like to develop rapport with study staff, and that one of the barriers to participation is the time commitment. The youth also provided feedback on the design of the clinical trial including outcome measurement tools, data collection, and engagement methods. Feedback on the virtual format of the engagement events indicated that participants appreciated the ease of the online discussion and that the open‐ended discussion allowed for easy exchange of ideas. They felt that despite a gender imbalance (towards females) it was an overall inclusive environment. All participants reported believing that their engagement will make a difference to the work of the research team in designing the clinical trials. Perspectives from a diverse group of youth meaningfully improved the design and conduct of two clinical trials for headaches in children. This study provides a framework for future researchers to engage youth in the co‐design of clinical trials using online engagement sessions.
Calculation ofthe transitions and migration of nitrogen and vacancy related defects,with implications on the formation of NV centers in bulk diamond

Formation and excitation energies as well charge transition levels, are determined forthe substitutional nitrogen (Ns),the vacancy (V) and related point defects (NV, NVH, N2, N2V and V2) by screened non-local hybrid density functional supercell plane wave calculations in bulk diamond. In additionthe activation energy for V and NV diffusion is calculated.We find good agreement between theory and experiment for the previously well-establisheddata, and predict missing ones. Based on the calculated properties of these defects, the formation of the negatively charged nitrogen-vacancy center is studied, which is a prominent candidate for application in quantum information processing and for nanosensors. We find that the concentration of NV defects are limited in natural diamonds due to the relatively high formation energy of NV. Our results imply that NV defects dominantly form just in the early stage of annealing in N-doped and irradiated diamonds. We find that the amphoteric divacancy defect with multiple acceptor states may significantly influence the charge state and photo-stability of NV in irradiated diamond samples.
A Novel Photovoltaic Consumption Capacity Evaluation Strategy Considering the Randomness of Source and Load

When distributed generation (DG) is connected to the distribution network, the transfer of power from the low- voltage power grid to the high-voltage power grid can result in detrimental effects on the power grid. Among various factors, power restriction is the primary factor that affects DG’s access to the distribution network. To address this, we establish a mathematical model that considers reverse power node voltage and power flow constraint to determine the maximum capacity of DG. Additionally, we introduce a hybrid approximation method to calculate the maximum access capacity. We validate the effectiveness of this approach through an example involving distributed photovoltaic (PV) generation accessing a 33-node low-voltage distribution network.
A Baseline Based User Invitation Aggregator Operation Approach

Demand response, as an important means of regulating the balance of the power system, can lead users to participate in market regulation. The discrete distribution of demand-side resources poses a challenge for electric utilities to directly invite customers. Aggregators, as intermediaries between the grid and customers, can efficiently realize demand-side resource management. In this paper, we propose a baseline-based aggregator operation strategy to ensure the profitability of the aggregator cycle by adopting a periodic settlement and a series of incentives and penalties. And a reasonable benefit allocation principle is formulated to ensure active participation of users in inviting responses and motivate them to respond.
Economic Issues Related to Continuous Supercritical Biodiesel Production

Commercially, the most common method of biodiesel production is alkali-catalyzed transesterification (Freedman et al, 1984, 1986). In this process a feedstock is reacted with alcohol in the presence of an alkali catalyst to yield biodiesel and glycerol. Virgin soybean oil is the most common feedstock used in commercial biodiesel production in the U.S. as it lends itself well to transesterification, is the largest source of vegetable oil, and allows for fast reaction times (Knothe, Jurgen and Van Gerpen, 2005; Ginder and Paulson, 2006). Alkali-catalyzed transesterification, however, requires expensive, refined feedstocks composed mainly of triglycerides and with low free fatty acid (FFA) content. This is because FFAs react with the alkali catalyst to form soaps that make it difficult to separate the biodiesel from the glycerol. The cost of virgin, low FFA feedstocks has limited the competitiveness of biodiesel, compared to petro-diesel, and is a barrier to its commercialization.
Characterization of surface ablation of dielectrics irradiated by 12-fs laser pulse in air

We develop an experiment of laser-matter interaction in air environment with ultrashort pulses of 12 fs in the context of micromachining. From post-mortem analysis of the sample, we determine the ablation thresholds of fused silica and sapphire exposed to single 12-fs laser pulse. We also analyze the evolution of macroscopic ablation quantities, taking into account the role of nonlinear propagation effects in air prior the target.
Groundedness in Logics With a Fixpoint Semantics

In the field of knowledge representation and reasoning, many different logics are developed. Often, these logics exhibit striking similarities, either because they emerged from related ideas, or because they use similar underlying fundamental principles. Approximation fixpoint theory (AFT) is an abstract algebraical unifying framework that aims at exposing these principles by formalising them in lattice theory. It has been successfully applied to unify all common semantics of logic programs, autoepistemic logic, default logic, and more recently Dung’s argumentation frameworks and abstract dialectical frameworks. In this dissertation, we extend approximation fixpoint theory to expose more underlying principles common to the aforementioned logics. In these domains, researchers have made use of a similar intuition: that facts (or models) can be derived from the ground up. They typically phrase this intuition by saying, e.g., that the facts should be grounded, or that they should not be unfounded, or that they should be supported by cycle-free arguments. In different domains, semantics that allow ungrounded models have received a lot of criticism. In logic programming for example, this was the case for Clark’s completion semantics, which was later improved by perfect model semantics, stable semantics and well-founded semantics. In autoepistemic logic, a similar evolution happened: Moore’s expansion semantics turned out to allow self-supporting models; this resulted in the development of many different semantics in attempts to get rid of this erroneous behaviour. In the first part of this dissertation, we formalise groundedness in approximation fixpoint theory. We study how groundedness relates to other concepts and fixpoints studied in AFT. We apply our abstract theory to the aforementioned domains: we show that our notion of groundedness indeed captures the intuitions that existed in these domains and study complexity of reasoning with grounded models. We study which existing semantics are grounded and which are not. For example, for logic programming, we find that Clark’s completion semantics (indeed) is not grounded, while stable and well-founded semantics are grounded.
Prediction of Gait Intention by Utilizing Pre-Movement EEG Signals: A Pilot Study

The electroencephalographic (EEG) activity from different parts of the brain areas can help understand and predict human decisions. The decision of gait intention in human mind is investigated in this pilot study using pre-movement EEG signals. In this early investigation, the authors collected EEG data from three subjects under two scenarios: the first is before making a planned movement, and the second is at rest, where no movement is planned. The experiments took place in indoor lab environment using OpenBCI EEG cap and Oculus VR headset. Using a 2s segment of the EEG recording, up to 98% classification accuracy was achieved by a Linear Discriminant Analysis (LDA) classifier, and an average of 90% accuracy was recorded among the three participants. These results demonstrate the potential of using an affordable and simple EEG acquisition system in predicting human movement, opening the door for further research to develop the framework for utilizing the technology in more realistic scenarios.