Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined Activity of Natural Products and the Fungal Entomopathogen Cordyceps farinosa against Bagrada hilaris (Hemiptera: Pentatomidae)

Abstract The invasive painted bug, Bagrada hilaris (Burmeister) (Hemiptera: Pentatomidae) is causing important losses in Brassica production. The main tool for management of this insect is the use of synthetic insecticides. There is an urgent need to find efficacious and environmentally friendly alternatives for its management. In this work, natural products (neem and lemongrass oils, and the microbial derivative spinosad) were tested separately and in combination with suspensions of infective conidia of the entomopathogenic fungus Cordyceps farinosa (Holmsk.) Kepler, Shrestha & Spatafora (Hypocreales: Cordycipitaceae) (strain ARSEF 13507) in the laboratory. The application of C. farinosa alone caused significant mortality. Regarding individual natural products, the highest mortality was obtained with spinosad. Neem oil alone caused low, non-significant mortality, and lemongrass oil alone caused low, marginally significant mortality. Both oils in combination with C. farinosa resulted in antagonistic effects, compared with the fungus alone. The combination of C. farinosa with spinosad resulted in increased insect mortality (20% and higher) compared with the separate agents. Our results indicate that spinosad (a high-price insecticide) should be tested in reduced amounts and combined with C. farinosa or possibly other entomopathogenic fungi, for control of painted bugs. Resumen La chinche pintada Bagrada hilaris (Burmeister) (Hemiptera: Pentatomidae) es un insecto invasor que causa pérdidas importantes en la producción de Brassica. La principal herramienta para su manejo es el control con insecticidas sintéticos. Urge encontrar alternativas eficaces y respetuosas con el medio ambiente para su manejo. En este trabajo, los productos naturales (aceites de neem y zacate limón o limoncillo, y el derivado microbiano spinosad) se probaron por separado y en combinación con suspensiones de conidias infectivas del hongo entomopatógeno Cordyceps farinosa (Holmsk.) Kepler, Shrestha & Spatafora (Hypocreales: Cordycipitaceae) (aislamiento ARSEF 13507) en el laboratorio. La aplicación de C. farinosa sola provocó mortalidad significativa. Con respecto a los productos naturales individuales, la mayor mortalidad se obtuvo con spinosad. El aceite de neem por sí solo causó mortalidad baja, no significativa y el de limncillo causó mortalidad baja, marginalmente significativa. Ambos aceites en combinación con C. farinosa produjeron efectos antagónicos, en comparación con el hongo solo. La combinación de C. farinosa con spinosad resultó en una mayor mortalidad de insectos (20% y más) en comparación con los agentes separados. Nuestros resultados indican que el spinosad (un insecticida de alto precio) debe probarse en cantidades reducidas, combinado con C. farinosa o posiblemente con otros hongos entomopatógenos, para el control de la chinche pintada.
GLACIAL VARIATIONS IN WEST GREENLAND IN POSTGLACIAL TIME

ABSTRACT A brief survey is made of the variations of the W. Greenland glaciers in post-glacial prehistoric and historic time. It is tentatively concluded that in post-glacial prehistoric time the variations were greater than in historic time, but varied in a uniform way parallel to the present ice margin. In historic time it appears that an advance commenced between 1500 and 1600, and an advance occurred in the 18th century. It is difficult to generalise about the maximum advances, there is a clear tendency for the maxima to occur before 1850 in the South, but in some other localities the maxima did not occur until 1900–1930.
Häufigkeit chronischer Schmerzen nach Arbeitsunfall – Eine erste Statuserhebung im BG-lichen Heilverfahren einer Tertiärklinik

Zusammenfassung Hintergrund Chronischer Schmerz ist nach Unfällen und Operationen eine Langzeitkomplikation, deren Relevanz für Patienten im BG-lichen Heilverfahren in Deutschland kaum untersucht ist. Fragestellung Erste Statuserhebung der Häufigkeit chronischer Schmerzen nach Arbeitsunfall. Methoden In 2017 wurden chirurgisch-stationäre BG-Patienten (18–65 J.) eines Tertiärkrankenhauses zu chronischen Schmerzen, die seit einem BG-lich anerkannten Trauma bestanden (Intervall 2,8±6,9 Jahre), ungeachtet einer stattgehabten Versorgung, erstmalig zum Zeitpunkt eines Krankenhausaufenthalts und dann telefonisch 6 Monate später befragt. Der Fokus lag auf Patienten mit einem Arbeitsunfall (A) innerhalb des letzten Monats oder (B) >6 Monaten. Primäres Outcome: Häufigkeit arbeitsunfallbedingter chronischer Schmerzen (>6 Monate) zum Initialinterview (Punktprävalenz), sekundäre Outcomes: Häufigkeit einer Chronifizierung nach 6 Monaten (A) und Persistenz chronischer Schmerzen (B). Tertiäre Outcomes: Arbeitsfähigkeit, Verletzungsartenverfahren, Auswirkungen anhand Schmerzintensität, -lokalisation und -medikation, Funktionseinschränkung in Abhängigkeit der Existenz chronischer Schmerzen sowie Komorbidität. Ergebnisse 415 Patienten wurden eingeschlossen, 85% (160/188) berichteten von unfallabhängigen chronischen Schmerzen (überwiegend mittlere bis sehr starke Intensität, an Gelenken und Knochen lokalisiert). 90% (131/145) gaben diese Schmerzen auch sechs Monate später an. 67% (64/96) gaben erstmalig chronische Schmerzen an. Patienten mit chronischen Schmerzen zum Follow-up (281/369) nahmen seltener ihre Berufstätigkeit wieder auf (p=0,003), in 60% Analgetika ein, waren öfter komorbide (p<0,002) und stärker in ihrer Extremitätenfunktionalität beeinträchtigt (p<0,002). Schlussfolgerung Auch wenn die Ergebnisse als vorläufig zu bewerten sind, scheinen chronische Schmerzen nach Arbeitsunfall sehr häufig und beeinflussen die Wiederherstellung der Arbeitsfähigkeit langfristig negativ. Anhand der vorliegenden anamnestischen Zahlen ist eine weiterführende differenzierte Reevaluation prospektiver Daten unter Beachtung therapeutischer Maßnahmen dringend anzuraten.
Arterial and Venous Thromboembolic Complications in 832 Patients with BCR-ABL -Negative Myeloproliferative Neoplasms

Abstract Arterial (ATE) and venous (VTE) thromboembolic complications are common causes of morbidity and mortality in BCR-ABL -negative myeloproliferative neoplasms (MPNs). However, there are few studies that include all MPN subtypes and focus on both MPN-associated ATE and VTE. In our single-center retrospective study of 832 MPN patients, a total of 180 first thromboembolic events occurred during a median follow-up of 6.6 years (range: 0–37.6 years), of which 105 were VTE and 75 were ATE. The probability of a vascular event at the end of the follow-up period was 36.2%, and the incidence rate for all first ATE/VTE was 2.43% patient/year. The most frequent VTE localizations were deep vein thrombosis with or without pulmonary embolism (incidence rate: 0.59% patient/year), while strokes were the most frequent ATE with an incidence rate of 0.32% patient/year. When comparing the group of patients with ATE/VTE ( n = 180) and the group without such an event ( n = 652) using multivariate Cox regression analyses, patients with polycythemia vera (hazard ratio [HR]: 1.660; [95% confidence interval [CI] 1.206, 2.286]) had a significantly higher risk of a thromboembolic event than the other MPN subtypes. In contrast, patients with a CALR mutation had a significantly lower risk of thromboembolism compared with JAK2 -mutated MPN patients (HR: 0.346; [95% CI: 0.172, 0.699]). In summary, a high incidence of MPN-associated VTE and ATE was observed in our retrospective study. While PV patients or generally JAK2 -mutated MPN patients had a significantly increased risk of such vascular events, this risk was reduced in CALR -mutated MPN patients.
Working with Mycorrhizas in Forestry and Agriculture

This manual is the result of an ACIAR-sponsored workshop to promote the use of mycorrhizal fungi for eucalypt plantation forestry in China. The manual explains procedures used by scientists who work with mycorrhizal fungi and roots in the laboratory, nursery, or natural and managed ecosystems. Forest nursery and plantation managers, horticulturists, agronomists, students and researchers will find it useful with many of the techniques used requiring readily obtainable and relatively inexpensive equipment and chemicals.
Reprogrammable non-linear circuits using ReRAM for NN accelerators

As the massive usage of Artificial Intelligence (AI) techniques spreads in the economy, researchers are exploring new techniques to reduce the energy consumption of Neural Network (NN) applications, especially as the complexity of NNs continues to increase. Using analog Resistive RAM (ReRAM) devices to compute Matrix-Vector Multiplication (MVM) in O(1) time complexity is a promising approach, but it’s true that these implementations often fail to cover the diversity of nonlinearities required for modern NN applications. In this work, we propose a novel approach where ReRAMs themselves can be reprogrammed to compute not only the required matrix multiplications, but also the activation functions, softmax, and pooling layers, reducing energy in complex NNs. This approach offers more versatility for researching novel NN layouts compared to custom logic. Results show that our device outperforms analog and digital Field Programmable approaches by up to 8.5x in experiments on real-world human activity recognition and language modeling datasets with Convolutional Neural Networks (CNNs), Generative Pre-trained Transformer (GPT), and Long Short-Term Memory (LSTM) models.
A Survey of Dataset Refinement for Problems in Computer Vision Datasets

Large-scale datasets have played a crucial role in the advancement of computer vision. However, they often suffer from problems such as class imbalance, noisy labels, dataset bias, or high resource costs, which can inhibit model performance and reduce trustworthiness. With the advocacy of data-centric research, various data-centric solutions have been proposed to solve the dataset problems mentioned above. They improve the quality of datasets by re-organizing them, which we call dataset refinement. In this survey, we provide a comprehensive and structured overview of recent advances in dataset refinement for problematic computer vision datasets1. Firstly, we summarize and analyze the various problems encountered in large-scale computer vision datasets. Then, we classify the dataset refinement algorithms into three categories based on the refinement process: data sampling, data subset selection, and active learning. In addition, we organize these dataset refinement methods according to the addressed data problems and provide a systematic comparative description. We point out that these three types of dataset refinement have distinct advantages and disadvantages for dataset problems, which informs the choice of the data-centric method appropriate to a particular research objective. Finally, we summarize the current literature and propose potential future research topics.
Combining Artificial Intelligence, Bio-Sensing and Multimodal Control for Bio-Responsive Interactives

We present framework and prototype process for combining affective bio-sensing, natural multimodal control, and artificial intelligence for bio-responsive interactives. The work explores a more affective, bio-responsive experience for users singularly or in multiuser environments in real-time and/or virtual reality (VR) interactives especially where mindfulness and wellness are a goal. The systems and framework can use EEG sensors, heart rate sensors, breath controllers and/or nature gesture controllers such as hand and body gestures. These bio-sensing and natural gestures inputs are combined with artificial intelligence generated musical and visual 2D or 3D forms where focused attention, embodiment and entrainment occurs to synchronization of the beats of music and generated 2D or 3D visuals with natural body function or processes. In this paper, we present our system framework and setup, as well as present our work-in-progress prototype.
Exploring Users' Pointing Performance on Virtual and Physical Large Curved Displays

Large curved displays have emerged as a powerful platform for collaboration, data visualization, and entertainment. These displays provide highly immersive experiences, a wider field of view, and higher satisfaction levels. Yet, large curved displays are not commonly available due to their high costs. With the recent advancement of Head Mounted Displays (HMDs), large curved displays can be simulated in Virtual Reality (VR) with minimal cost and space requirements. However, to consider the virtual display as an alternative to the physical display, it is necessary to uncover user performance differences (e.g., pointing speed and accuracy) between these two platforms. In this paper, we explored users’ pointing performance on both physical and virtual large curved displays. Specifically, with two studies, we investigate users’ performance between the two platforms for standard pointing factors such as target width, target amplitude as well as users’ position relative to the screen. Results from user studies reveal no significant difference in pointing performance between the two platforms when users are located at the same position relative to the screen. In addition, we observe users’ pointing performance improves when they are located at the center of a semi-circular display compared to off-centered positions. We conclude by outlining design implications for pointing on large curved virtual displays. These findings show that large curved virtual displays are a viable alternative to physical displays for pointing tasks.
Detection and evaluation of signals associated with exposure to individual and combination of medications in pregnancy: a signal detection study protocol

Introduction Considering the high prevalence of polypharmacy in pregnant women and the knowledge gap in the risk–benefit safety profile of their often-complex treatment plan, more research is needed to optimise prescribing. In this study, we aim to detect adverse and protective effect signals of exposure to individual and pairwise combinations of medications during pregnancy. Methods and analysis Using a range of real-world data sources from the UK, we aim to conduct a pharmacovigilance study to assess the safety of medications prescribed during the preconception period (3 months prior to conception) and first trimester of pregnancy. Women aged between 15 and 49 years with a record of pregnancy within the Clinical Practice Research Datalink (CPRD) Pregnancy Register, the Welsh Secure Anonymised Information Linkage (SAIL), the Scottish Morbidity Record (SMR) data sets and the Northern Ireland Maternity System (NIMATS) will be included. A series of case control studies will be conducted to estimate measures of disproportionality, detecting signals of association between a range of pregnancy outcomes and exposure to individual and combinations of medications. A multidisciplinary expert team will be invited to a signal detection workshop. By employing a structured framework, signals will be transparently assessed by each member of the team using a questionnaire appraising the signals on aspects of temporality, selection, time and measurement-related biases and confounding by underlying disease or comedications. Through group discussion, the expert team will reach consensus on each of the medication exposure–outcome signal, thereby excluding spurious signals, leaving signals suggestive of causal associations for further evaluation. Ethics and dissemination Ethical approval has been obtained from the Independent Scientific Advisory Committee, SAIL Information Governance Review Panel, University of St. Andrews Teaching and Research Ethics Committee and Office for Research Ethics Committees Northern Ireland (ORECNI) for access and use of CPRD, SAIL, SMR and NIMATS data, respectively.
Lightweight Symphony: Towards Reducing Computer Science Student Anxiety with Standardized Docker Environments

During the COVID-19 pandemic, remote learning (RL) transformed the educational landscape for hands-on Computer Science courses. This paradigm shift accelerated the transition from traditional in-person programming labs to decentralized student-provided resources. Even as students returned to in-person learning, many continued to rely on their personal computers rather than embracing university-provided labs. However, this shift to decentralized, heterogeneous environments introduced a variety of information technology and instructional challenges. The recent emergence of lightweight, container-based virtualization presents a unique opportunity to address these challenges by offering standardized environments on decentralized platforms. To investigate this opportunity, we implemented lightweight virtualization for three undergraduate computer science courses with a total enrollment of 188 students. To understand the challenges and successes of implementing these environments, we surveyed 42 students before, during, and after the three courses. Our survey responses identified that 84% of students adopted our standardized environments, with 75% indicating it contributed to their success. We believe that sharing our experience will prove valuable for instructors who wish to explore adopting container-based virtualization to reduce student anxiety in the modern classroom.
Use of Visual Research Methods to Measure Standards of Quality for Parks and Outdoor Recreation

Visual research methods have been adapted and incorporated into measuring standards of quality for parks and outdoor recreation. This paper reviews and assesses this research. Visual research methods offer several potential advantages over conventional narrative/numerical questions to measure standards of quality. For example, visual methods can help “standardize” such research, focus more directly and exclusively on the treatment variables under study, offer a more elegant means of communicating variables that are difficult or awkward to describe in narrative/numerical terms, and can be used to represent conditions that are difficult to find in the field or that do not currently exist. Research suggests that visual research methods may be most appropriate in frontcountry or other high use density contexts, may result in more valid or realistic estimates of visitor standards of quality in such applications, meet generally accepted standards of validity, and may be methodologically robust. Technological and societal trends suggest that visual research methods may continue to evolve into more dynamic formats and offer opportunities for expanded applications in the future.
Open Video Game Library: Developing a Video Game Database for Use in Research and Experimentation

Video games are utilized in some studies for evaluation experiments and demonstrations. However, because commercial video games cannot be edited, optimizing them for specific experiments is challenging. Thus, researchers may have to develop their own video games individually, which requires effort and impedes the comparison of their study with other similar studies. To overcome these limitations, in this study, we propose a user-friendly "Open Video Game Library" that can be used by researchers for experiments. We conducted a survey of previous studies and designed video games to meet researcher needs. The library features characteristics such as GUI-based parameter editing, play log output, open-source availability, and support for operation on multiple devices, with the aim of becoming the de facto standard for video games used for research purposes.
Prevalence of non-communicable diseases and risk factors of pre-eclampsia/eclampsia in four local government areas in Nigeria: a cross-sectional study

Objectives To assess the prevalence of non-communicable diseases (NCDs) and risk factors associated with pre-eclampsia and eclampsia (PE/E) in women of reproductive age (WRA) in Nigeria. Design A cross-sectional survey was administered to the entire study population. In the point-of-care testing, physical and biochemical measurements were taken in a subset of the participants. Setting The study was conducted in the Ikorodu and Alimosho local government areas (LGAs) in Lagos and the Abuja Municipal Area Council and Bwari LGAs in the Federal Capital Territory. Participants Systematic random sampling was used to randomly select and recruit 639 WRA (aged 18–49 years) between May 2019 and June 2019. Outcome measures Prevalence of select NCDs (hypertension or raised blood pressure, diabetes or raised blood sugar levels, anaemia, truncal obesity and overweight/obesity) and risk factors associated with PE/E (physical activity, fruit and vegetable consumption, alcohol consumption and smoking). Results The prevalence of raised blood pressure measured among the WRA was 36.0% (95% CI 31.3% to 40.9%). Approximately 10% (95% CI 7.2% to 13.4%) of participants had raised blood sugar levels. About 19.0% (95% CI 15.3% to 23.2%) of the women had moderate or severe anaemia. Excluding WRA who were pregnant, 51.9% (95% CI 45.7% to 58.0%) of the women were either overweight or obese based on their body mass index. Approximately 58.8% (95% CI 53.8% to 63.6%) of WRA surveyed reported three to five risk factors for developing NCDs and PE/E in future pregnancies. Conclusions The study identified a high prevalence of NCDs and associated PE/E risk factors in surveyed women, signifying the importance of early detection and intervention for modifiable NCD and associated PE/E risk factors in WRA. Further research is necessary to assess the national prevalence of NCDs.
A Heterogeneous Unmanned Ground Vehicle and Blimp Robot Team for Search and Rescue using Data-driven Autonomy and Communication-aware Navigation

: This paper describes the architecture and implementation of a heterogeneous team comprising unmanned ground vehicles and blimp robots capable of navigating unknown subter-ranean environments for search and rescue missions. The ground vehicles are equipped with a range of sensors for accurate perception, localization, and mapping. The blimps feature a long ﬂight duration and collision tolerance when traversing uneven terrain. The design of the system was meant to satisfy the requirements of the Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge in terms of perception capability and autonomy. To facilitate navigation through smoke-ﬁlled spaces, we employed novel millimeter wave radar to enable cross-modal representations for integration via deep reinforcement learning. The autonomy of the proposed scheme was augmented using simulations to train deep neural networks, thereby allowing the system to perform sequential decision-making for collision avoidance and navigation toward a speciﬁc goal. The navigation system was evaluated in the DARPA SubT Urban Circuit, and quantitative localization results and recovery strategy from failures was discussed. The proposed communication system comprises mesh WiFi with XBee (ZigBee network with XBee radios) and
Velocity and concentration profiles in sheet-flow layer of movable bed

Sheet-flow layer of movable bed in steady currents has been investigated experimentally, using four kinds of sediment. Velocity and concentration profiles as well as flow resistance were measured inside and outside the sheet-flow layer. The range of fall-velocity–to–friction-velocity ratio ( w /U f) achieved in the study is 0.2 0.8–1). In the suspension-mode sheet flow, the flow resistance is found to depend not only on the Shields parameter but also on a parameter involving w . Measured velocity profiles are found to follow the logarithmic law near the bed, outside the sheet-flow layer, whereas inside the sheet-flow layer, they satisfy a power law. Measured concentration profiles, on the other hand, indicate a linear variation with the distance from the bed inside the sheet flow-layer near the bed, whereas away from the bed, the familiar Rouse distribution is sat.