ethicalabs/Research-Intent-Collab huggingface dataset:
Integrating Weed Biological Control Agents into a Pest-Management Program

Little effort has been directed toward integrating biological control; that is, the use of living natural enemies to control weeds, with more conventional weed control practices. The usual focus of biological control has been on the introduction of weed insects and pathogens from foreign areas to control naturalized range, pasture, and/or aquatic weeds, principally single species that had become dominant over a plant community. The released natural enemies were allowed to reach their own balance with the target weed without added assistance. As economic and environmental perspectives change along with our knowledge and technological capability, however, it becomes worthwhile to review periodically if and how biological control might be integrated with other farming practices. Because my biological control experience has centered on the use of weed-feeding insects, this discussion will focus on methods of enhancing and integrating insect impact on weeds with other weed-control activities.
Learning Analytics: The Role of Information Technology for Educational Process Innovation

Today, trends and advancements in information and communication technologies have proven to be indispensable towards achieving the goals of modern educational models and processes. On the one hand, there is a need for educators to adopt new technologies in support of different activities that constitute the educational processes; ranging from the changing higher institutional labour market to the rapid renovation of information systems and tools used to support the learners. Moreover, such a requirement also relates to the several educational communities that are expected to include a more proactive and creative learning strategies and experiences for the stakeholders (e.g. teachers and students). On the other hand, this paper shows that to meet those needs, Learning Analytics (LA) which implies measurement, collection, analysis, and reporting of data about the progress of stakeholders and contexts in which learning takes place is of importance. To this end, this paper proposes a Learning Analytics Educational Process Innovation model (LAEPI) that leverages the ever-increasing amount of data that are recorded and stored about the different learning activities and digital footprints of users within the educational settings. This is done in order to provide a method that shows to be useful towards maintaining a continuous improvement and monitoring of the educational processes or platforms. Thus, the term Educational Process Innovation. Technically, the work illustrates implication of the method in real-time using dataset about online learning activities of university students for its experimental analysis and results.
An Investigation of Lean Application Challenges in Construction Projects by Root Cause Analysis

The construction industry has increasingly embraced lean construction methodologies to improve productivity, minimize waste, and enhance stakeholder value. Despite this growing trend, several challenges hinder the successful adoption of Lean Principles in developing countries. Within the Kurdistan Region of Iraq, the implementation of lean construction remains constrained by multiple barriers that have not been systematically examined. In this study, the challenges associated with lean construction adoption are explored through the application of Root Cause Analysis (RCA) techniques, including fishbone diagrams, Pareto charts, and the "5 Whys" method. RCA provides a structured and analytical approach for identifying the fundamental causes of systemic issues and determining their relative significance. The identified challenges are classified into five main categories: organizational, cultural and human attitudes, technical, governmental and regulatory, and financial. A total of forty-one challenges were recorded, among which twenty-eight were recognized as key obstacles to lean implementation. Moreover, an innovative methodological approach is introduced by focusing on the underlying causes rather than superficial manifestations of lean construction barriers in developing contexts. The findings offer valuable insights for policymakers, project managers, and industry stakeholders, enabling the formulation of targeted strategies that address systemic obstacles, promote organizational transformation, and establish a conducive environment for the effective implementation of lean practices.
Antimicrobial Resistance (AMR) Crisis Novel Strategies for Antibiotic Stewardship and Discovery

The purpose of the study was to examine the knowledge, attitudes, and behaviors of the population against antibiotic use and antimicrobial resistance (AMR) and analyze how such factors as age, education, and awareness campaigns influence antibiotic misuse. Structured questionnaires were used to survey 250 samples consisting of patients and general people in Punjab, Pakistan. Using descriptive statistics, 46 percent of the respondents advised on inappropriate use of antibiotics like taking them without prescription or failing them, among others. Pearson correlation demonstrated that there is a definite positive connection between knowledge and attitudes (r = .482, p &lt; .01) i.e. more informed people displayed more responsible attitudes regarding AMR. The regression analysis revealed that both age (0.241, p = .001) and the educational level (0.289, p = .001) were predictors of misuse power but the segment occupation type was not significant (0.132, p = .080). The model was significant, 26.3 of the variance was explained in the misuse behavior. Due to the significant difference in the tendency to use antibiotics without proper reasons among people who were exposed to awareness campaigns (chi-square = 12.346, p&lt;.001) the results of the chi-square analysis were presented along with the mentioning of the significance value, p &lt;.001. The results are consistent with previous research that identifies the power of the education of the population in managing AMR. These outcomes imply that the misuse of antibiotics can be decreased by raising awareness, enhancing access to the right information, and educating every population group, in particular, younger generations. The study recommends beefed-up public health promotion, increased regulatory control of prescriptions, and policy-based preventive measures that would avert the increasing risks of antimicrobial resistance.
Biopesticides and biological control agents: advances, integration, and prospects for sustainable pest management

Agrifood demand has intensified due to increasing global population, resulting in widespread reliance on synthetic insecticides for pest control in both open-field and greenhouse systems. Although these insecticides have significantly contributed to agricultural productivity, their intensive and prolonged use has resulted in pest resistance, high production costs, disruption of non-target organisms, and risks to human health. Consequently, there is an urgent need for safer, cost-effective, and more environmentally sustainable pest control alternatives. In this context, biopesticides have emerged as promising alternatives to conventional synthetic insecticides, due to their lower toxicity to non-target organisms, rapid biodegradability, decreased environmental persistence, and greater compatibility with biological control agents within integrated pest management (IPM) programs. Biopesticides encompass a diverse range of products, including biochemical compounds, microbial agents, botanical formulations, and plant-incorporated protectants. Recent innovations in formulation and delivery technologies have significantly enhanced the efficacy and stability of biopesticides. For example, nano-formulated products, such as nano-encapsulated                     Bacillus thuringiensis                     , have demonstrated up to a 30–50% increase in field persistence and pest control efficacy compared to conventional formulations. This review extensively discusses biopesticide classification and relationship to biological control, modes of action, advantages, current, in front of limitations, and roles in modern agriculture. It further examines recent developments in formulation and delivery technologies, alongside regulatory, commercial, and agroecological factors influencing adoption. Finally, our review emphasizes the critical role of biopesticides in decreasing reliance on synthetic chemicals, enhancing agroecosystem resilience, and supporting the global transition toward sustainable and eco-friendly plant protection systems.
Abstract 13898: Redo Catheter Ablation for Atrial Fibrillation: Assessment of Quality of Life and Clinical Outcomes Using Patient Reported Outcomes

Background:             Catheter ablation for symptomatic atrial fibrillation (AF) is frequently used for sustained rhythm control and improved quality of life (QoL). Although success rates are high, a significant proportion of patients require redo ablation. Data is scarce on patient-centered outcomes in patients undergoing redo AF ablation.                                   Objective:             To investigate QoL and clinical outcomes using a large prospectively maintained automated patient reported outcomes (PRO) database.                                   Methods:             All patients undergoing redo AF ablation (2013-2016) at our center were enrolled and assessed for QoL effect using automated PRO surveys (baseline, 3 and 6 months after ablation, every 6 months thereafter). This analysis included data over 3 years of follow-up. The atrial fibrillation severity scale (AFSS) was used as the main measure for QoL assessment. Additional variables collected included patient-reported clinical improvement, AF burden, as well as AF related healthcare utilization including ER visits and hospitalizations.                                   Results:             A total of 848 patients were included (28% females, mean age 63.8, 51% persistent AF). By automated PRO, significant improvement in QoL was noted (baseline median AFSSS of 12 [5-18] and ranged between 2 and 4 on subsequent assessments; P&lt;0.0001), with ≥70%of patients reported marked improvement in their overall AF-related symptoms. The proportion of patients in AF at the time of completion of the baseline survey was 36%, and this decreased to &lt;8% across all time points during follow-up (P&lt;0.0001). Further, AF burden was significantly reduced (including frequency and duration of episodes; P&lt;0.0001), with associated decrease in healthcare utilization after 6 months from the time of ablation (including ER visits and hospitalizations; P&lt;0.0001). The proportion of patients on anticoagulants, antiarrhythmics, or rate control medications decreased on follow-up across all time points (P&lt;0.0001 for all variables).                                   Conclusions:             Most patients derive significant QoL benefit from redo AF ablation. A fully automated PRO system enhanced collection of AF-specific outcomes and showed improvement in QoL, AF burden, and healthcare utilization after redo ablation procedures.
DIFFERENCES AND SIMILARITES BETWEEN TOTAL QUALITY MANAGEMENT, ISO 9001, LEAN PRODUCTION, AND SIX SIGMA

Abstract: Total quality management is a management approach with the goal to achieve customer satisfactionthrough product, service, and organizational culture improvement. ISO 9000 is a set of international standards thatis developed for achieving an effective quality management system in order to satisfy customer needs. The concept oflean production is described as a systematic approach to reduce the number of defect products, and reduce the sizeof the warehouse, without lowering productivity. Six sigma includes tools, and techniques for improving processesregarding quality, and reducing the number of defect products. In this paper the differences, and similarities of totalquality management, ISO 9001, lean production, and six sigma, will be investigated. The paper presents the criteriafor successful implementation, and use of the mentioned concepts in various companies. The amount of risk thateach concept brings is also evaluated. The goal of the paper is an analytic approach, and a concise description ofquality management systems, and business performance imrpovement.
Inter-charge forces in relativistic classical electrodynamics: electromagnetic induction in different reference frames

The force due to electromagnetic induction on a test charge is calculated in different reference frames. The Faraday-Lenz Law and different formulae for the fields of a uniformly moving charge are used. The classical Heaviside formula for the electric field of a moving charge predicts that, for the particular spatial configuration considered, the inductive force vanishes in the frame in which the magnet is in motion and the test charge at rest. In contrast, consistent results, in different frames, are given by the recently derived formulae of relativistic classical electrodynamics.
Distributed Kaplan-Meier Analysis via the Influence Function with Application to COVID-19 and COVID-19 Vaccine Adverse Events

During the COVID-19 pandemic, regulatory decision-making was hampered by a lack of timely and high-quality data on rare outcomes. Studying rare outcomes following infection and vaccination requires conducting multi-center observational studies, where sharing individual-level data is a privacy concern. In this paper, we conduct a multi-center observational study of thromboembolic events following COVID-19 and COVID-19 vaccination without sharing individual-level data. We accomplish this by developing a novel distributed learning method for constructing Kaplan-Meier (KM) curves and inverse propensity weighted KM curves with statistical inference. We sequentially update curves site-by-site using the KM influence function, which is a measure of the direction in which an observation should shift our estimate and so can be used to incorporate new observations without access to previous data. We show in simulations that our distributed estimator is unbiased and achieves equal efficiency to the combined data estimator. Applying our method to Beaumont Health, Spectrum Health, and Michigan Medicine data, we find a much higher covariate-adjusted incidence of blood clots after SARS-CoV-2 infection (3.13%, 95% CI: [2.93, 3.35]) compared to first COVID-19 vaccine (0.08%, 95% CI: [0.08, 0.09]). This suggests that the protection vaccines provide against COVID-19-related clots outweighs the risk of vaccine-related adverse events, and shows the potential of distributed survival analysis to provide actionable evidence for time-sensitive decision making.
VideoElevator: Elevating Video Generation Quality with Versatile Text-to-Image Diffusion Models

Text-to-image diffusion models (T2I) have demonstrated unprecedented capabilities in creating realistic and aesthetic images. On the contrary, text-to-video diffusion models (T2V) still lag far behind in frame quality and text alignment, owing to insufficient quality and quantity of training videos. In this paper, we introduce VideoElevator, a training-free and plug-and-play method, which elevates the performance of T2V using superior capabilities of T2I. Different from conventional T2V sampling (i.e., temporal and spatial modeling), VideoElevator explicitly decomposes each sampling step into temporal motion refining and spatial quality elevating. Specifically, temporal motion refining uses encapsulated T2V to enhance temporal consistency, followed by inverting to the noise distribution required by T2I. Then, spatial quality elevating harnesses inflated T2I to directly predict less noisy latent, adding more photo-realistic details. We have conducted experiments in extensive prompts under the combination of various T2V and T2I. The results show that VideoElevator not only improves the performance of T2V baselines with foundational T2I, but also facilitates stylistic video synthesis with personalized T2I. Please watch all videos in supplementary materials for better view.
Applications and future prospects of artificial intelligence in the diagnosis and prognosis of lung cancer

With its annual incidence gradually rising and hence a major threat to public health, lung carcinoma is a major contributor to cancer-associated death worldwide. Artificial intelligence (AI) in computer science refers to research on robots, language processing, image recognition, speech, and machine learning (ML) applications. This will change the physician’s approach to cancer management. Given its successful application in many healthcare fields, AI has recently made significant developments. In lung cancer, this development is especially important because AI has shown great efficiency in therapeutic strategies and diagnostic techniques. This review aims to present a brief overview of AI approaches applied in the field of lung cancer. We discuss the foundations of AI, deep learning (DL), image identification, natural language processing, and human-computer interfaces. The most recent AI advancements and their applications in lung cancer diagnosis, treatment, and prognosis were also examined in this study. Finally, we address the difficulties in applying AI and how it can affect clinical practice in lung cancer.
Corporate social responsibility reporting by the National Forest Holding „State Forests”

Today, the company, in addition to meeting its economic goals, should be involved in the implementation of the concept of corporate social responsibility. State Forests is not an exception in this respect, on the contrary – its existence, by definition, has dictated inscribing in the mission, vision and strategy of this company a responsibility to society, both to present and future generations. To date, State Forests has not developed a uniform framework for reporting socially responsible activities. Despite the many scattered documents indicating their contribution in this regard, State Forests has not included in its report a set of information on these issues. The aim of the article is to point out that social responsibility in such an entity as State Forests National Forest Holding is an extremely important area having long-term conse-quences for the contemporary and future generations. The article demonstrates the need for corporate social responsibility accounting and proposes a general structure of a report on social responsibility of State Forests for the current and future stakeholders. As a primary method of research, in addition to literature studies, the deductive method was used, assisted with reasoning by analogy.
Pengaruh Information Quality, System Quality, Dan Usefulness Terhadap Kinerja Sumber Daya Manusia Melalui Human Resource Information System (HRIS) Succes Pada Masa Pandemi Covid19 (Studi Pada PT. Bank Ganesha Tbk)

Tujuan dari penelitian ini adalah untuk mengidentifikasi pengaruh kualitas informasi, kualitas sistem dan kegunaan terhadap kinerja melalui keberhasilan HRIS di PT. Bank Ganesha Tbk. Pengujian hipotesis da-lam penelitian ini menggunakan metode SEM yang didukung oleh aplikasi SPSS 21 dan AMOS 22. Penelitian ini menggunakan 3 variabel independen dengan variabel intervening keberhasilan HRIS dan variabel dependen kinerja. Teknik pengumpulan data dalam penelitian ini menggunakan data primer dengan menyebarkan kuesioner kepada 135 pegawai Bank Ganesha. Karakteristik sampel yang ditentukan dalam penelitian ini meliputi pegawai tetap, telah bekerja minimal 1 tahun dan menggunakan BIPO HRMS. Berdasarkan hasil penyaringan responden yang telah dilakukan, ditetapkan bahwa hanya 129 dari 135 responden yang memenuhi syarat. Hasil penelitian ini menunjukkan bahwa 1) Kualitas Informasi ber-pengaruh negatif signifikan terhadap Keberhasilan HRIS, 2) Sistem Kualitas tidak berpengaruh terhadap Keberhasilan HRIS, 3) Kegunaan berpengaruh positif signifikan terhadap keberhasilan HRIS, 4) Keber-hasilan HRIS tidak berpengaruh terhadap kinerja, 5) Kualitas Informasi berpengaruh negatif signifikan ter-hadap kinerja melalui Keberhasilan HRIS, 6) Kualitas Sistem menghasilkan berpengaruh positif signifikan langsung terhadap kinerja, 7) Kegunaan berpengaruh positif signifikan terhadap kinerja melalui HRIS Suc-cess.
Environmentally induced migration and the concepts vulnerability, resilience and adaptation to climate change

Diese Arbeit beschäftigt sich mit dem komplexen Zusammenhang zwischen menschlicher Migration und Klimawandel. Ökologische Faktoren und im speziellen Klimawandel haben unterschiedliche Auswirkungen auf verschiedene soziale Gruppen und sozi-ökologische Systeme. Ein Ziel dieser Arbeit ist es zu zeigen welche Rolle die ausgewählten Konzepte Vulnerabilität, Resilienz und Anpassung bezüglich der Auswirkungen von Klimawandel spielen. Eine Reihe von teilweise ähnlichen, teilweise sehr unterschiedlichen Theorien und Ansätze wird deshalb auf ihre Rolle bezüglich Auswirkungen von Klimawandel untersucht. Speziell die Implikationen der Theorien auf mögliche Migrationsentscheidungen werden untersucht. Das zweite Bestreben dieser Forschung ist es zu untersuchen wie die Konzepte Vulnerabilität, Resilienz und Anpassung in relevanten Policy Empfehlungen vorkommen und was die Konzepte in ihrer jeweiligen Form implizieren. Um diese Forschungsfrage zu beantworten wird eine qualitative Inhaltsanalyse im zweiten Teil der Arbeit durchgeführt. Die beiden letzten Assessement Reports des Intergovernmental Panel on Climate Change (IPCC), veröffentlich 2001 und 2007, stellen ein gutes Datenmaterial für die angestrebte Untersuchung dar. Die beiden analysierten IPCC Berichte demonstrieren die ausschlaggebende Rolle von ökonomischen Faktoren für den jeweiligen Grad von Vulnerabilität und Resilienz, jedoch betont der vierte Assessment Report von 2007 die Wichtigkeit von sozialen und institutionellen Parametern. Diese Abkehr von einseitig ökonomistischen Erklärungsmustern stellt den größten Unterschied zwischen den beiden IPCC Berichten dar. Die Ergebnisse dieser Recherche implizieren, dass die alarmistischen Vorhersagen von zusätzlichen Millionen Flüchtlingen auf Grund von verstärktem Klimawandel simplifizierend sind. Klimawandel stellt bezüglich des multikausalen Phänomens Migration lediglich einen zusätzlichen Faktor dar. Jedoch kann dieser zusätzliche Faktor in Kontexten von ohnehin sozial und politisch angespannten Situationen eine zusätzliche Belastung bedeuten.
Wideband study of the brightest black hole X-ray binary 4U 1543−47 in the 2021 outburst: signature of disc-wind regulated accretion

ABSTRACT                A comprehensive wideband spectral analysis of the brightest black hole X-ray binary 4U 1543−47 during its 2021 outburst is carried out for the first time using NICER, NuSTAR, and AstroSat observations by phenomenological and reflection modelling. The source attains a super-Eddington peak luminosity and remains in the soft state, with a small fraction ($\lt 3{{\ \rm per\ cent}}$) of the inverse-Comptonized photons. The spectral modelling reveals a steep photon index (Γ ∼ 2–2.6) and relatively high inner disc temperature (Tin ∼ 0.9–1.27 keV). The line-of-sight column density varies between (0.45–0.54) × 1022 cm−2. Reflection modelling using the RELXILL model suggests that 4U 1543−47 is a low-inclination system (θ ∼ 32°–40°). The accretion disc is highly ionized (log ξ &amp;gt; 3) and has super solar abundance (3.6–10 AFe,⊙) over the entire period of study. We detected a prominent dynamic absorption feature between ∼8 and 11 keV in the spectra throughout the outburst. This detection is the first of its kind for X-ray binaries. We infer that the absorption of the primary X-ray photons by the highly ionized, fast-moving disc winds can produce the observed absorption feature. The phenomenological spectral modelling also shows the presence of a neutral absorption feature ∼7.1–7.4 keV, and both ionized and neutral absorption components follow each other with a delay of a typical viscous time-scale of 10–15 d.