Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Dilated Hierarchical Filter Based 3D U-Net for Multi-Modal Brain Tumor Segmentation

Brain tumor segmentation is an essential task in the field of medical image analysis. Brain lesions (e.g. gliomas) have various shapes, sizes, and locations between different patients, making it challenging localizing and doing other tasks. For a single tumor, the essential contextual information may inhabit much larger regions than itself. Multi-scale feature representation can improve model generalization. However, existing U-Net models perform with layer-wise features. In this paper, a 3D multi-dilated hierarchical filter module is proposed based on hierarchical multi-scale strategy and multi-fiber strategy. The main points of our proposed module are multi hierarchical filter connection and multi-branch dilated convolutions. Besides, the proposed module is applied with a 3D U-Net. The results of experiments on the validation subset of BraTS2018 dataset show the efficacy of the proposed module.
Model Development and Predictive Control of a Low-Inertia DC Solid-State Transformer (SST)

In this article, a dynamic model is developed for a low-inertia dc solid-state transformer (SST) formed by inductor-less modular multilevel converters (MMCs) based on phase-shifted square-wave modulation (PS-SWM). Unlike other SSTs, both power flow and circulating energy need to be controlled quickly and accurately to achieve high performance during both transients and steady state. The developed model explicitly defines the circulating energy and retains its accuracy with an arm inductor-less operation. Furthermore, the model can be treated as time-invariant under square-wave modulation and analyzed in the small-signal domain to obtain system transfer functions, allowing small-signal analysis. Based on the developed model, predictive control is designed to achieve fast dynamic control with reduced computational burden. In addition, a feedforward current control is proposed to suppress the steady-state current harmonics of the dc current caused by the enlarged circulating energy due to the low-inertia feature. A medium-voltage dc (MVDC) simulation case study and experimental results on downscaled low-inertia SST hardware are provided to validate the developed model and the predictive controller performance.
Design of Indoor Localization Algorithm Based on WiFi Fingerprints

WiFi-based indoor localization has been deeply studied and researched due to the convenient deployment of the WLAN infrastructure. However, indoor localization based on WiFi suffers the fluctuation of Received Signal Strength (RSS), including missing RSS during collection, redundant Access Points (APs), and abnormal RSS values. Therefore, in this paper, we propose a hybrid filtering algorithm based on isolated forest and weighted mean to ensure the real-time filtering correction of RSS signal and provide high-quality fingerprint signal for online location. In addition, a two-panel fingerprint homogeneity graph is adopted to gauge the resemblance of localization fingerprints, and the estimated 2-D location is predicted by the integration of panel results. We have conducted experiments to demonstrate the localization algorithm’s performance. Compared with other algorithms, the results show that the proposed method can achieve the best performance.
Extraperitoneal Laparoscopic Prostatectomy in a Prostate Cancer Patient Undergoing Continuous Ambulatory Peritoneal Dialysis

Radical prostatectomy (RP) in patients on continuous ambulatory peritoneal dialysis (CAPD) is a challenging procedure. The following key points need to be considered: the peritoneal cavity integrity, adjustment of the trocar positions to the peritoneal dialysis (PD) tube location, and the oncological and functional outcomes. We present a clinical case of a patient on CAPD, incidentally diagnosed with prostate cancer (PCa) during the pre-transplant evaluation. The patient suffered from LUTS, due to bladder outlet obstruction (BOO). A transurethral bladder neck incision (TUNI), with median lobe resection, was performed. A PCa Gleason score of six (3 + 3) was found in the histopathological specimen. The primary procedure was complicated by bladder neck sclerosis and acute urinary retention (AUR), resolved by suprapubic cystostomy. After proper staging determination, the patient was qualified for laparoscopic extraperitoneal RP. The standard trocar placement was modified to align with the route of the PD tube, and Retzius’ space scarring was released to allow extraperitoneal prostatectomy. There were no signs of peritoneal wall damage or dialysis tube displacement. Peritoneal dialysis was resumed after 4 weeks. Laparoscopic extraperitoneal RP should be considered as an acceptable treatment method for selected patients with localized prostate cancer, allowing CAPD resumption. To the best of our knowledge, this is the first report of retroperitoneal laparoscopic RP being used in the PD population.
Physical Therapist Management of Patients With Suspected or Confirmed Osteoporosis: A Clinical Practice Guideline From the Academy of Geriatric Physical Therapy

A clinical practice guideline on physical therapist management of patients with suspected or confirmed osteoporosis was developed by a volunteer guideline development group (GDG) that was appointed by the Academy of Geriatric Physical Therapy (APTA Geriatrics). The GDG consisted of an exercise physiologist and 6 physical therapists with clinical and methodological expertise. The guideline was based on a systematic review of existing clinical practice guidelines, followed by application of the ADAPTE methodological process described by Guidelines International Network for adapting guidelines for cultural and professional utility. The recommendations contained in this guideline are derived from the 2021 Scottish Intercollegiate Guideline Network (SIGN) document: Management of Osteoporosis and the Prevention of Fragility Fractures. These guidelines are intended to assist physical therapists practicing in the United States, and implementation in the context of the US health care system is discussed.
PENGARUH PENERAPAN ETIKA BISNIS ISLAM TERHADAP KINERJA USAHA MIKRO KECIL DAN MENENGAH

This research aims to determine the extent of the influence of the application of Islamic business ethics on the performance of Small and Medium Enterprise (SME). The research method used in this research is quantitative research with multiple linear regression analysis based on multiple linear regression analysis obtained partial and simultaneous effect. The results of the accepted hypothesis or variables that have a positive and significant effect on the performance variables, namely the aspect of fairness, free will, responsibility, Tauhid and Ihsan have a significant positive effect on the performance of Small and Medium Enterprise (SME). Simultaneously all aspects of Islamic business ethics affect performance with a coefficient of determination of 0.746 or 74.6%. The independent variable that has the most dominant influence on performance is seen from the Standardized Coefficients Beta test by looking at the value of the Standardized Coefficients Beta the largest is the responsibility variable with a value of 0.475 greater than the other variables.
Distributed Circle Formation Control for Quadrotors Based on Multi-agent Deep Reinforcement Learning

Multi-rotor unmanned aerial vehicles (UAVs) have been increasingly used in both civil and military applications in recent years, and it is difficult for a single multi-rotor UAV to accomplish a specific task due to the load and range limitations. In this paper, we take the most commonly used quadrotor among multi-rotor UAVs as the research object, and study the formation control problems such as formation generation, formation transformation and collision avoidance. We design a distributed circle formation algorithm based on deep reinforcement learning, which is combined with an artificial potential based law to ensure collision avoidance. In order to simulate the real environments, a multi-quadrotor simulator is built based on ROS and gazebo. The algorithm is trained and tested in the simulator, whose results show the effectiveness of the proposed algorithm.
The effect of recombinant chimeric swine PKR-Apaf-1 proteins on viral-load reduction of PRRS and PED alpha-coronavirus infected cell lines

The PRRS virus and PED alpha-coronavirus are the two main pig pathogens in the world. The current strategies to control these diseases are inadequate. The recombinant chimeric swine PKR-Apaf-1 protein (rcPAP) consists of the Human Immunodeficiency Virus Trans-activator transcription (HIV-TAT) domain, the dsRNA-binding domain of porcine Protein kinase R (PKR) gene and the caspase recruitment domain (CARD) domain of porcine Apoptotic Protease-Activating Factor-1 (Apaf-1) gene. In general, the rcPAP can detect viral dsRNA in virally infected cells and induces apoptosis and kills the virus-infected cells. In this study, the reducing viral-load efficacy of rcPAP (produced from bacteria) against PRRS virrus and PED alpha-coronavirus replication in the cell line was studied. The four concentrations of rcPAP (40, 60, 80 and 120 μg/ml) were studied at three different periods (24, 36 and 48 h post inoculation (hpi)). The results showed that no cytotoxicity in two cell lines was observed during rcPAP addition. The rcPAP (80 μg/ml) significantly increased the monkey active caspase-3 levels at 17.09 for the PRRS virus and at 15.96fold for the PED alpha-coronavirus at 48 hpi, respectively (p < 0.05). The viral RNA copy numbers at 48 hpi were significantly reduced up to 84.47% of PRRS virus and up to 82.98% for PED alpha-coronavirus when treated with rcPAP (80 μg/ml) (p < 0.05), respectively. Interestingly, the viral titers at 48 hpi were dramatically decreased by 87.76% for PRRS virus and by 86.29% for PED alpha-coronavirus in virus-infected cells treated with rcPAP (80 μg/ml), respectively. The results also demonstrated that the rcPAP was able to reduce the viral load and viral N protein synthesis in both virus-infected cell lines. In conclusion, the results suggest that rcPAP is likely to be a valuable therapeutic agent against both PRRS virus and PED alpha-coronavirus infection.
Exploring strategies for management of disasters associated with illegal gold mining in abandoned mines: A case study of Ekurhuleni Metropolitan Municipality

Due to many abandoned mines that are not rehabilitated, there will be illegal mining. Although the mining industry and government continue to prevent illegal gold mining in abandoned mines by sealing open shafts, it is not possible to close all the shafts at once due to limited resources. Furthermore, after sealing the shafts, illegal miners often create alternative openings to enter underground workings while little or nothing is being done to stop the surface illegal gold mining. As long as illegal gold mining is there, disasters associated with illegal mining are prevalent. Effective disaster preparedness and response requires a competent strategy. The purpose of this study was to develop a strategy that can be used for emergency preparation and rescue efforts associated with disasters caused by abandoned mines and illegal gold mining. In this qualitative study, semi-structured interviews were held with officials and experts on disaster management from the Council for Geoscience and the City of Ekurhuleni. This study indicates that the safety of illegal miners and communities near abandoned mines depends on several factors including the ability to identify and respond to a disaster. The study identified three interlinked themes within the report as strategies for dealing with disasters related to abandoned mines and illegal gold mining. These themes included emergency countermeasures and short-term measures, roles and responsibilities and communication. These interlinked themes should be validated through further research that involves input from the national disaster response community at large. This study will serve as a model that can be implemented in other areas impacted by illegal mining in South Africa.
EFFECTIVENESS OF THE NATIONAL MARINE SANCTUARY PROGRAM IN ADDRESSING OCEAN NOISE EFFECTS ON MARINE MAMMALS

Ocean noise has become a persistent global threat to marine mammal habitats. U.S. National Marine Sanctuaries have been regarded as possible ocean noise mitigation tools because of their special focus on conservation of marine resources and their location within key marine mammal habitats; yet previous evaluations of National Marine Sanctuaries have not focused specifically on their effectiveness in addressing ocean noise and its impacts on marine mammals. Using management plan and survey data of 11 U.S. National Marine Sanctuaries, this study investigates 1) the actions that Sanctuaries are taking to address ocean noise impacts from human activities on marine mammals and 2) the effectiveness of the U.S. National Marine Sanctuary Program at managing noise impacts on marine mammals. Findings indicate that the Program overall is moving toward effectiveness by conducting research, management, and education or outreach related to ocean noise and marine mammals. However, some individual Sanctuaries could take more action to mitigate ocean noise and the National Marine Sanctuary Program could increase its ocean noise education and outreach. Evaluation of Sanctuary ocean noise mitigation actions is crucial to ensure that Sanctuaries are fulfilling their purpose of protection and conservation by responding to emerging threats such as ocean noise pollution.
Audio-Visual Based Online Multi-Source Separation

Meeting or conference assistance is a popular application that typically requires compact configurations of co-located audio and visual sensors. This paper proposes a novel solution for online separation of an unknown and time-varying number of moving sources using only a single microphone array co-located with a single visual device. The approach exploits the complementary nature of simultaneous audio and visual measurements, accomplished by a model-centric 3-stage process of detection, tracking, and (spatial) filtering, which performs separation in a block-wise or recursive fashion. Fusing the measurements requires solving the multi-modal space-time permutation problem, since the audio and visual measurements reside in different observation spaces, but also are unidentified or unlabeled (with respect to the unknown and time-varying number of sources), and are subject to noise, extraneous measurements and missing measurements. A labeled random finite set tracking filter is applied to resolve the permutation problem and recursively estimate the source identities and trajectories. A time-varying set of generalized side-lobe cancellers is constructed based on the tracking estimates to perform online separation. Evaluations are undertaken with live human speakers.
Multi-agent Collaborative Adaptive Cruise Control Based On Reinforcement Learning

With the development and application of intelligent networked vehicles, Adaptive Cruise Control (ACC) is gradually developed and upgraded to Cooperative Adaptive Cruise Control (CACC). However, in the CACC system, following error, relative speed and acceleration have a certain range of constraints. If the acceleration fluctuates and amplifies backwards along the queue and violates the saturation constraint boundary, the acceleration of the vehicle behind will increase continuously, and the system will lose the stability of the queue and cause traffic accidents. Therefore, based on the Model Predictive Control (MPC) theory, this paper takes the CACC system as the research object and adopts the form of weighted quadratic performance functional and linear matrix inequality constraints. The design problem of the ACC is finally transformed into an online convex quadratic programming problem with constraints. At the same time, the saturation control of the CACC system is studied based on the parametric Lyapunov equation to improve the stability of the system.
STAT2: Building Models for a World of Data

W.H. Freeman, 2012. 2012. 624 pages. 1464148260, 9781464148262. STAT2: Building Models for a World of Data. Ann R. Cannon, George W. Cobb, Bradley A. Hartlaub, Robin H. Lock, Julie M. Legler. STAT2 is designed to help students build on their statistical knowledge in order to analyze rich datasets using statistical models. The book develops a systematic approach to using different models and includes exercises to allow students to practice working with real data alongside output from statistical software. file download cywu.pdf
Visualisation to Aid Decision-Making for Time-Quality Tradeoffs In Search

We present the results of two studies for an experimental setup that offers a tradeoff between time and result quality, and gives participants a visualisation of the expected quality of results in an optional sidebar before they begin their task. We investigate the effects of the type of visualisation we show to participants of a crowdsourced survey, and find that the type of visualisation presented had no significant effects on their perceptions of quality, but observed that there was value in offering a visualisation versus none at all. We also performed a pilot study that fixes the visualisation type and manipulates the estimation of future quality such that it conveys either an accurate estimate of quality, an overestimate, or an un-derestimate of quality. The results of clickstream and gaze tracking data analysis point towards potential effects on usage and attention to the optional sidebar, suggesting the utility of a full-scale study.
Aminoacyl-tRNA Synthetase: A Non-Negligible Molecule in RNA Viral Infection

Infectious diseases such as the ongoing coronavirus disease 2019 (COVID-19) continue to have a huge impact on global health, and the host-virus interaction remains incompletely understood. To address the global threat, in-depth investigations in pathogenesis are essential for interventions in infectious diseases and vaccine development. Interestingly, aminoacyl-transfer RNA (tRNA) synthetases (aaRSs), an ancient enzyme family that was once considered to play housekeeping roles in protein synthesis, are involved in multiple viral infectious diseases. Many aaRSs in eukaryotes present as the components of a cytoplasmic depot system named the multi-synthetase complex (MSC). Upon viral infections, several components of the MSC are released and exert nonenzymatic activities. Host aaRSs can also be utilized to facilitate viral entry and replication. In addition to their intracellular roles, some aaRSs and aaRS-interacting multi-functional proteins (AIMPs) are secreted as active cytokines or function as “molecule communicators” on the cell surface. The interactions between aaRSs and viruses ultimately affect host innate immune responses or facilitate virus invasion. In this review, we summarized the latest advances of the interactions between aaRSs and RNA viruses, with a particular emphasis on the therapeutic potentials of aaRSs in viral infectious diseases.
Diversity and distribution of arbuscular mycorrhizal Vigna fungi associated with Bambara groundnut ( subterranea (L.) Verdcourt ) in Benin

Bambara groundnut, despite its attributes in providing protein to human, is facing soil fertility and degradation problems, always leading to little performances. Arbuscular mycorrhizal fungi (AMF) constitute a microorganism group used by many researchers to improve productivity of crops in poor soils. This study aimed to evaluate the distribution and diversity of AMF associated to Bambara groundnut in different agro-ecological zones in Benin. A survey was conducted through 20 villages chosen based on Bambara groundnut yield, cropping area and its production across five agroecological zones (from AEZ 1 to AEZ 5). Soil and root samples were collected to assess spore density and diversity, root colonization levels and soil chemical properties. Results revealed significant difference (p <0.0001) among agro-ecological zones in terms of density of AMF, which varied from 2825 to 5713 spores per 100 g of soil, depending on the AEZ. The highest density was recorded in the cotton zone in the northern Benin. The diversity of AMF also varied, depending on the AEZ. In total, 14 morphotypes belonging to five genera (Glomus, Gigaspora, Acaulospora, Scutellospora and Diversispora) were identified in the different studied zones with Glomus genus the most frequently recorded in all AEZ. Correlation tests among the different parameters have, in general, revealed that, the zones with the low rates of the different parameters had those with the highest frequencies of mycorrhization. It also appears that spore density did not correlate with diversity index, mycorrhization frequencies and intensities, but soil chemical parameters significantly did.
Competence and performance

The general notions of “competence” and “performance” are variously invoked as a way of drawing attention to at least a few specific distinctions. There are certain common threads running through the various uses of the terms, and from a sufficiently zoomed-out view they can be construed as manifestations of a single underlying distinction. But when these over-arching, general terms are so frequently invoked across a variety of contexts, the details of what is at issue in each instance can become obscured. In this chapter I will focus on pulling apart some of the different bifurcations that the labels “competence” and “performance” have been used to highlight. Roughly following Phillips (1996, pp.275–277), I identify these three:1 • The distinction between sentences that are grammatical and sentences that are parsable. • The distinction between what speakers can do and what speakers choose to do. • The distinction between static/declarative knowledge and procedural/operational knowledge.
Following the crowd: Anomalies and crowding by Institutional Investors

This paper investigates the relation between crowded trades, those in which many investors hold the same stocks possibly exhausting their liquidity provision, and institutional investors’ trading activity on a set of twelve well-known stock market anomalies. We find that anomaly risk-adjusted returns appear to be concentrated among the most (least) crowded stocks for the long-leg (short-leg) portfolio Moreover, we find that our results remain significant after publication dates and are stronger among holdings of transient institutions. We hypothesize that crowded equity positions in anomaly stocks increase institutional investor’s exposure to crash risk and fire sales which adds a new consideration to the limits of arbitrage.
Science in Russia and the Soviet Union: A Short History by Loren R. Graham (review)

Preface Illustrations Introduction Part I. The Tsarist Period: 1. Russian science before 1800 2. Science in nineteenth-century Russia 3. Russian intellectuals and Darwinism Part II. Russian Science and a Marxist Revolution: 4. The Russian Revolution and the scientific community 5. The role of dialectical materialism: the authentic phase 6. Stalinist ideology and the Lysenko affair Part III. Science and Soviet Society: 7. Soviet attitudes towards the social and historical society 8. Knowledge and power in Russian and Soviet science 9. The organizational features and Soviet science Conclusion Appendices Notes Bibliographical essay Index.