Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Driven Risk-Adjusted Robust Energy Management for Microgrids Integrating Demand Response Aggregator and Renewable Energies

Microgrids, integrating user-side demand response and zero marginal cost renewable energies, are potential components for future smart grids to reduce carbon emissions and improve power system resilience. In this paper, a day-ahead microgrid energy management framework with demand response aggregator as an intermediate coordinator is developed. The corresponding scheduling strategy is obtained to maximize the social welfare of the microgrid system, with considering the privacy of end-users and the uncertainty of renewable energies. To this end, firstly, a accelerated distributed optimization method based on Alternating Direction Method of Multipliers, named as FAST-PP-ADMM, is developed to protect the end-users privacy and improve the scalability of the microgrid system. Secondly, a data-driven risk-adjusted uncertain set is constructed with a distributionally robust chance-constraints model to characterize the forecast error of renewable energies. Based on the constructed uncertain set, a two-stage robust microgrid-side energy management model is solved by using the column-and-constraint generation (C&CG) method. Finally, the effectiveness of the proposed energy management framework and scheduling strategy is verified by simulations.
Supply chain visibility for improving inbound logistics: a design science approach

ABSTRACT Supply chain visibility (SCV) has been gaining recognition in recent years as a key factor for achieving analytical capabilities and improving supply chain performance. However, levels of SCV implementation lag behind current technological advances. This research was motivated by the lack of visibility in inbound logistics, which limits the possibility of managing deviation, in particular concerning changes in arrival time of incoming goods, in large industrial firms. We addressed this problem by adopting a design science approach. In particular, we followed context–intervention–mechanism–outcome (CIMO) logic to map and analyse material and information flows. The problems areas were successively translated via business and functional requirements into technological solutions. We evaluated alternative technologies using controlled experiments that mimicked real-life situations. This study provides guidance for manufacturing companies aiming to enhance deviation management and predictive capabilities by improving visibility in their inbound logistics and potentially extending visibility to other areas, such as internal and outbound flows.
A novel communication‐aware adaptive key management approach for ensuring security in IoT networks

Internet of Things (IoT) encompasses heterogeneous communication devices and wireless technologies to provide ubiquitous access using end‐user devices. It operates on a common website for connecting versatile devices with seamless communication, data access and sharing. Communication through wireless medium requires enormous security features to protect both public and private data across different interconnected resources. Therefore, in this article, a communication‐aware adaptive key management (CAKM) is proposed to ensure two levels of security in IoT communication. The two‐levels of security include both device and message that is facilitated using certificate authority and key management. By exploiting the benefits of hyper elliptic curve cryptography (HECC), the communication‐aware adaptive key management ensures message authentication for the device requests. Initially, the device requests are classified on the basis of its service time and correlated to the time‐to‐live period of the certificate. The proposed method attains low computational time 10.9%, 30.2%, and 54.3%, high security level 10.9%, 30.2%, and 54.3%, high successful message rate 10.9%, 30.2%, and 54.3% and low key agreement time 10.9%, 30.2%, and 54.3% when compared to the three existing methods, such as bilateral generalization inhomogeneous short integer solution (Bi‐GISIS)‐based key management in IoT security (Bi‐GISIS‐IoT), hyper elliptic curve based public key cryptosystem in IoT security (HCCPK‐IoT) and enhanced symmetric key‐based authentication in IoT security (ESKA‐IoT). Finally, the proposed method provides an efficient security with low computational time.
Novel p38 Mitogen-Activated Protein Kinase Inhibitor Reverses Hypoxia-Induced Pulmonary Arterial Hypertension in Rats

Mitogen-activated protein kinase (MAPK) signaling is strongly implicated in cardiovascular remodeling in pulmonary hypertension (PH) and right ventricle (RV) failure. The effects of a newly designed p38 inhibitor, LASSBio-1824, were investigated in experimentally induced PH. Male Wistar rats were exposed to hypoxia and SU5416 (SuHx), and normoxic rats were used as controls. Oral treatment was performed for 14 days with either vehicle or LASSBio-1824 (50 mg/kg). Pulmonary vascular resistance and RV structure and function were assessed by echocardiography and catheterization. Histological, immunohistochemical and Western blot analysis of lung and RV were performed to investigate cardiovascular remodeling and inflammation. Treatment with LASSBio-1824 normalized vascular resistance by attenuating vessel muscularization and endothelial dysfunction. In the heart, treatment decreased RV systolic pressure, hypertrophy and collagen content, improving cardiac function. Protein content of TNF-α, iNOS, phosphorylated p38 and caspase-3 were reduced both in lung vessels and RV tissues after treatment and a reduced activation of transcription factor c-fos was found in cardiomyocytes of treated SuHx rats. Therefore, LASSBio-1824 represents a potential candidate for remodeling-targeted treatment of PH.
A 4-Tap CMOS Time-of-Flight Image Sensor with In-pixel Analog Memory Array Achieving 10Kfps High-Speed Range Imaging and Depth Precision Enhancement

This paper presents a new 4-tap indirect Time-of-Flight (TOF) image sensor with in-pixel analog memory array and sub-frame integration achieving up to 10Kfps high-speed range imaging with 8 recording frames and 1.67% depth noise from 0.4-1.5m. This sensor also operates with an improved depth precision of 1.3% from 0.4-4.2m at 90fps by averaging the in-pixel memory. 85% demodulation contrast was obtained at 80MHz modulation frequency owing to the 4-tap charge modulator with high-speed charge collection photodiode.
Research on 3D Point Cloud Data Preprocessing and Clustering Algorithm of Obstacles for Intelligent Vehicle

Environment perception is the foundation of the intelligent driving system and is a prerequisite for achieving path planning and vehicle control. Among them, obstacle detection is the key to environment perception. In order to solve the problems of difficult-to-distinguish adjacent obstacles and easy-to-split distant obstacles in the traditional obstacle detection algorithm, this study firstly designed a 3D point cloud data filtering algorithm, completed the point cloud data removal of vehicle body points and noise points, and designed the point cloud down-sampling method. Then a ground segmentation method based on the Ray Ground Filter algorithm was designed to solve the under-segmentation problem in ground segmentation, while ensuring real time. Furthermore, an improved DBSCAN (Density-Based Spatial Clustering of Application with Noise) clustering algorithm was proposed, and the L-shaped fitting method was used to complete the 3D bounding box fitting of the point cloud, thus solving the problems that it is difficult to distinguish adjacent obstacles at close distances caused by the fixed parameter thresholds and it is easy for obstacles at long distances to split into multiple obstacles; thus, the real-time performance of the algorithm was improved. Finally, a real vehicle test was conducted, and the test results show that the proposed obstacle detection algorithm in this paper has improved the accuracy by 6.1% and the real-time performance by 13.2% compared with the traditional algorithm.
New Generation Express View: An Artificial Intelligence Software Effectively Reduces Capsule Endoscopy Reading Times

BACKGROUND: Reading capsule endoscopy (CE) is time-consuming. The Express View (EV) (IntroMedic, Seoul, Korea) software was designed to shorten CE video reading. Our primary aim was to evaluate the diagnostic accuracy of EV in detecting significant small-bowel (SB) lesions. We also compared the reading times with EV mode and standard reading (SR). METHODS: 126 patients with suspected SB bleeding and/or suspected neoplasia were prospectively enrolled and underwent SB CE (MiroCam®1200, IntroMedic, Seoul, Korea). CE evaluation was performed in standard and EV mode. In case of discrepancies between SR and EV readings, a consensus was reached after reviewing the video segments and the findings were re-classified. RESULTS: The completion rate of SB CE in our cohort was 86.5% and no retention occurred. The per-patient analysis of sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of EV compared to SR were 86%, 86%, 90%, 81%, and 86%, respectively, before consensus. After consensus, they increased to 97%, 100%, 100%, 96%, and 98%, respectively. The median reading time with SR and EV was 71 min (range 26–340) and 13 min (range 3–85), respectively (p < 0.001). CONCLUSIONS: The new-generation EV shows high diagnostic accuracy and significantly reduces CE reading times.
Overcoming Temozolomide Resistance in Glioblastoma via Enhanced NAD+ Bioavailability and Inhibition of Poly-ADP-Ribose Glycohydrolase

Simple Summary Glioblastoma is the most prevalent and lethal brain tumor type, often treated with the DNA alkylating agent temozolomide (TMZ). The cytotoxic DNA lesion O6-methylguanine only accounts for about 9% of the DNA lesions induced by TMZ. The other DNA lesions (>80%) are quickly repaired by the base excision repair (BER) pathway. However, resistance to cytotoxicity of the O6-methylguanine lesion is common in cancer due to defects in the mismatch repair pathway or overexpression of the MGMT repair protein. Therefore, the aim of this study was to find approaches to inhibit the BER pathway to overcome TMZ resistance. We found that combining TMZ with an NAD+ precursor (dihydronicotinamide riboside) and a PARG inhibitor strongly inhibited BER and overcame TMZ resistance. This combination treatment regimen provides a novel approach to consider for glioblastoma. Abstract Glioblastoma multiforme (GBM) is an incurable brain cancer with an average survival of approximately 15 months. Temozolomide (TMZ) is a DNA alkylating agent for the treatment of GBM. However, at least 50% of the patients treated with TMZ show poor response, primarily due to elevated expression of the repair protein O6-methylguanine-DNA methyltransferase (MGMT) or due to defects in the mismatch repair (MMR) pathway. These resistance mechanisms are either somatic or arise in response to treatment, highlighting the need to uncover treatments to overcome resistance. We found that administration of the NAD+ precursor dihydronicotinamide riboside (NRH) to raise cellular NAD+ levels combined with PARG inhibition (PARGi) triggers hyperaccumulation of poly(ADP-ribose) (PAR), resulting from both DNA damage-induced and replication-stress-induced PARP1 activation. Here, we show that the NRH/PARGi combination enhances the cytotoxicity of TMZ. Specifically, NRH rapidly increases NAD+ levels in both TMZ-sensitive and TMZ-resistant GBM-derived cells and enhances the accumulation of PAR following TMZ treatment. Furthermore, NRH promotes hyperaccumulation of PAR in the presence of TMZ and PARGi. This combination strongly suppresses the cell growth of GBM cells depleted of MSH6 or cells expressing MGMT, suggesting that this regimen may improve the efficacy of TMZ to overcome treatment resistance in GBM.
Trust and Power in the Space Between Visibility and Invisibility. Exploring Digital and Social Media Practices in Norwegian Child Welfare Services

ABSTRACT In this article, we explore how caseworkers in the Norwegian Child Welfare Services and their clients use digital and social media in information sharing. By applying Foucault’s description of Bentham’s Panopticon as an analytical tool, we show how caseworkers’ use of digital and social media without the client’s knowledge, while making themselves invisible, contribute to increase the power asymmetry of a professional–client relationship. The clients, on the other hand, have less possibilities of making themselves invisible. If they discover that caseworkers have invaded their private information, this is experienced as a breach of trust. While some studies discuss the equalising potential of using digital and social media in welfare communication, this study reveals some of the pitfalls in using these medias for communication and information exchange. Regardless of the type of media in question, their use becomes vital for visibility, trust and power. Our findings underscore that it is not only the digital tools that needs regulation. Regulations should address the participation of clients in deciding on communication tools and the all-important openness and non-covert practices necessary to build and maintain trusting relationships between caseworkers and clients.
Novel techniques for stabilizing fiber laser frequency combs

We present the carrier envelope offset (CEO) frequency stabilization of a fiber laser using two novel methods. The first one is based on cross gain modulation (XGM) implemented with a low-power auxiliary light sharing the laser gain medium. The second method is based on opto-optical-modulation (OOM) of a semiconductor absorber mirror in the laser cavity, used for the first time in a fiber laser. We achieved CEO stabilization with feedback bandwidths of up to 600 kHz using these two easy-to-integrate methods. A tight CEO lock was achieved with a residual integrated phase noise of less than 400 mrad.
Hip and Knee Joint Angles Determine Fatigue Onset during Quadriceps Neuromuscular Electrical Stimulation

Neuromuscular electrical stimulation (NMES) has been used to increase muscle strength and physical function. However, NMES induces rapid fatigue, limiting its application. To date, the effect of quadriceps femoris (QF) muscle length by knee and hip joint manipulation on NMES-induced contraction fatigability is not clear. We aimed to quantify the effects of different muscle lengths on NMES-induced contraction fatigability, fatigue index, and electromyographic (EMG) activity for QF muscle. QF maximum evoked contraction (QMEC) was applied in a 26 min protocol (10 s on; 120 s off; 12 contractions) in 20 healthy participants (24.0 ± 4.6 years old), over 4 sessions on different days to test different conditions. The tested conditions were as follows: supine with knee flexion of 60° (SUP60), seated with knee flexion of 60° (SIT60), supine with knee flexion of 20° (SUP20), and seated with knee flexion of 20° (SIT20). Contraction fatigability (torque decline assessed by maximal voluntary contraction [MVC] and during NMES), fatigue index (percentage reduction in MVC), and EMG activity (root mean square [RMS] and median frequency) of the superficial QF' constituents were assessed. After NMES, all positions except SUP20 had an absolute reduction in MVC (p < .001). Fatigue index was greater in SIT20 than in SIT60 (p < .001) and SUP20 (p = .01). There was significant torque reduction across the 12 QMEC in SUP60 and SIT60, up to 10.5% (p < .001–.005) and 9.49% (p < .001–.033), respectively. There was no torque reduction during NMES in SUP20 and SIT20. Fatigue was accompanied by an increase in RMS (p = .032) and a decrease in median frequency for SUP60 (p < .001). Median frequency increased only in the SUP20 condition (p = .021). We concluded that QF NMES-induced contraction fatigability is greater when the knee is flexed at 60° compared to 20°. In addition, a supine position promotes earlier fatigue for a 60° knee flexion, but it delays fatigue onset for a 20° knee flexion compared to the seated position. These results provide a rationale for lower limb positioning during NMES, which depends on training objectives, e.g., strengthening or task-specific functionality training.
Joint Scheduling of Proactive Pushing and On-Demand Transmission Over Shared Spectrum for Profit Maximization

Proactive pushing has emerged as a promising solution to scale the service capacity by utilizing idle spectrum resources when on-demand transmission cannot fully exploit the spectrum resources during off-peak times. How to schedule both pushing and on-demand transmission jointly to meet a higher spectrum efficiency becomes a critical issue. Moreover, efficient and fair spectrum sharing among multiple resource schedulers remains open. In this paper, we introduce virtual network operators (VNOs) as schedulers that pay for consumed bandwidth and jointly schedule pushing and on-demand services. We adopt nonlinear spectrum pricing schemes with a convex and increasing price function enabling each VNO to share spectrum resources appropriately and independently. Considering the revenue from users and the cost for spectrum, we formulate a Markov decision process (MDP) to maximize the profit of VNO. A modified value iteration algorithm is applied to solve the MDP with reduced computational complexity. Furthermore, we show the structure of the optimal policy and provide the upper and lower bounds for the optimal performance. We present a low-complexity heuristic policy that can scale in practice with large state spaces and action spaces.
Complete chloroplast genome of an invasive marine macroalga Ulva californica (Ulvophyceae, Chlorophyta)

Abstract Species belonging to Ulva (Ulvophyceae, Chlorophyta) are one of the major members of invasive seaweeds. Ulva californica Wille 1899 was originally believed to be native to the Pacific coast of North America, while in recent years it has been reported as exotic species, or new record, in Europe, the Mediterranean, Asia, and Oceania. However, the paths of global dispersal of U. californica are unclear. In addition, the species boundary between U. californica and a related species is somewhat disputed. Here, we reported that the complete chloroplast genome of U. californica is 92,126 bp in size, harboring 96 genes (GenBank accession no. MZ561475). The overall base composition was A (37.9%), T (37.4%), C (12.3%), and G (12.4%), similar to those from other Ulva species. The phylogenomic analysis showed that although U. californica was genetically closer to Ulva aragoënsis (Bliding) Maggs 2018 in [Krupnik N et al., 2018], they were clearly distinguishable, supporting the recent opinion that they should be separated into different species. The chloroplast genome data of U. californica would provide plenty resources for phylogeography analysis and monitor on bioinvasion.
Workspace and Productivity: Guidelines for Virtual Reality Workplace Design and Optimization

Employee satisfaction and productivity are highly dependent on the alignment between the design of a workplace, the culture, the work activities, and the technology used, and while the understanding of such interactions has received increased interest in fields including architecture, health, and psychology, very little is known in relation to virtual work and reality (VR). VR workplaces have the potential to become an integral part of new work arrangements, enabling employees to execute teamwork and task work through (mature) simulated environments designed to meet individual, team, and organizational productivity needs. Thus, the aim of this study was three-fold: In study 1, we gained, through expert interviews, insights into contemporary thinking in workplace design, and gathered a greater understanding of the dimensions of design, behaviors, environments, and tools that affect collaborative work and productivity. In study 2, we observed knowledge workers in home environments and open, closed, and balanced office layouts, in order to understand the potential for successful integration in VR. In study 3, we evaluated environmental needs and opportunities through VR. Based on our findings, we developed an Ecology of Work model, combining work systems and pillars of performance success. These are followed by discussions on design needs and implications for VR.
A Coherent Approach to Evaluating Precipitation Forecasts over Complex Terrain

Precipitation forecasts provided by high-resolution NWP models have a degree of realism that is very appealing to most users of meteorological data. However, it is a challenge to demonstrate whether or not such forecasts contain more skillful information than their lower resolution counterparts. A verification procedure must be based on equally detailed observations that are also realistic in areas where ground observations are not available and remote sensing data can only increase the accuracy of the location of rain events at the cost of decreased accuracy in estimating the amount of rain that has actually reached the ground. Traditional verification methods based on station or grid point comparison yield poor results for high-resolution fields due to the double penalty error that is attributed to finite space and time displacement that such methods do not account for. A complete approach to evaluating precipitation forecasts over complex terrain is suggested. The method is based on realistic gridded precipitation observations generated by an interpolation method that uses long climate data series to determine the geographical characteristics that this parameter is best correlated with as well as remote sensing estimates as background information to cover the areas where observations are insufficient. Spatial verification methodologies are subsequently applied to a convective event that accentuate the relative skill of high-resolution COSMOGR forecasts in revealing characteristics in the precipitation patterns such as structure and intensity.
Identifying the optimal characteristics of ball possession and movement in elite women’s soccer

ABSTRACT The aim of this study was to determine whether the ball passing characteristics of elite women’s soccer teams are associated with measures of team performance. In total, 170 matches from two professional women’s competitions were used in the analysis. Twenty passing characteristics were analysed to determine their association with match outcome and two score-related variables, shots on target and big chances. The value of 18 passing characteristics was different between teams that won or lost their match, when both leagues were analysed together. When the leagues were analysed separately, there were only three characteristics whose value was consistently higher for teams that won; proportions of passes in the defensive third, successful long passes and successful backward passes. Regression models demonstrated that there were relationships between passing characteristics and measures of team performance, such as shots on target (r 2 = 0.434, p < 0.001). The present findings provide evidence of the optimal passing characteristics in elite women’s soccer teams, which include; more total passes, minimising short passes but maximising their success and the success of long and backward passes. These results provide valuable information regarding the construction of team tactics and strategy of ball movement that is effective and specific to elite women’s soccer.