bluuebunny/crossref_metadata_2025 huggingface dataset:
Phase II trial of ArtemiCoffee for men with biochemical recurrence of prostate cancer after local therapy.
Authors: Myint Zin , St. Clair William H , Strup Stephen , Hensley Patrick J. , Yan Donglin , Ellis Carleton Scott , Kolesar Jill
Published: January 2024

TPS350

Background: The optimal timing for initiating androgen deprivation therapy (ADT) in biochemical recurrent (BCR) prostate cancer (PC) patients, specifically those with PSA doubling time > 10 months, remains uncertain. Therefore, there is a compelling need for clinical trials exploring alternatives to ADT. Artesunate, derived from Artemisinin which is extracted from Artemisia annua (Aa), shows anti-cancer effects. Aa comprises several active constituents including dihydroartemisinic acid, artemisinic acid, and artemisinin. Our research group assessed the sensitivity of prostate cancer cells to Artesunate using established PC cell lines such as LNCaP, C4-2, CWR-22Rv1 and PC-3. Two cell lines, LNCaP (PSA and AR positive, hormone naïve) with an IC50 of 3.30 µM (95% CI 2.28-4.79) and C4-2 (PSA and AR positive, castration resistant) with an IC50 of 3.99 µM (3.13-5.10 µM) demonstrated sensitivity to Artesunate. Wang et. al (2017) reported that Artesunate, administered at varying doses, effectively suppressed tumor growth, inhibited cell viability and enhanced apoptosis in a mouse xenograft model using the 22rv1 PC cell line. Based on these promising preclinical findings, we hypothesize that Aa decaf coffee has the potential to decrease rising PSA levels in patients with BCR PC. Our research group previously conducted a phase I dose escalation of ArtemiCoffee in ovarian cancer (NCT04805333) and preliminary results indicated no grade ≥3 toxicities at the proposed dose (unpublished data). In this study, we aim to conduct a phase II study of Aa decaf coffee in men with BCR PC. Methods: An open-label, single center, phase II study targets men with BCR PC following primary definitive local therapy and a PSA doubling time > 10 months. Commercially available Aa decaf coffee pods supplied by ArtemiLife Inc. will be utilized. These decaf coffee pods adhere to FDA food-grade quality standards and Aa plants used for ArtemiLife coffee are cultivated in Kentucky, USA. Aa decaf coffee will be self-administered three times daily (total of 1,350mg Aa) on an outpatient basis for 24 weeks. The primary endpoint is to determine the proportion of patients achieving a ≥50% decline in PSA levels within 24 weeks of Aa decaf coffee treatment in BCR population. A total of 30 patients will be enrolled in this study, ensuring a maximum margin of error of approximately 16% in the 95% confidence interval for the primary endpoint. Secondary endpoints include safety and tolerability. Correlative endpoints include 1) changes in downstream biomarkers of the NRF2/KEAP1 signaling pathway and 2) changes in plasma concentrations of artemisinin and dihydroartemisinin by comparing pre- and post-treatment with Aa decaf coffee using non-parametric paired test. The study commenced accrual in August 2023. Clinical trial information: NCT05478239 .
Phase II study of axitinib intensification compared to nivolumab alone after induction with ipilimumab plus nivolumab in patients with mRCC without previous complete response (AxIn study).
Authors: Ciccarese Chiara , Verzoni Elena , Bimbatti Davide , Buti Sebastiano , Calabrò Fabio , Galli Luca , Scagliarini Sarah , Fornarini Giuseppe , Baldessari Cinzia , Bilancia Domenico , Facchini Gaetano , Cattrini Carlo , Masini Cristina , Giganti Maria Olga , Scandurra Giuseppa , Nole Franco , Berruti Alfredo , Milella Michele , Antonuzzo Lorenzo , Iacovelli Roberto
Published: January 2024

TPS494

Background: The combination of nivolumab plus ipilimumab (N+I) is able to increase the overall survival (OS), progression free survival (PFS) and overall response rate (ORR) compared to sunitinib in patients (pts) with metastatic renal cell carcinoma (mRCC) at intermediate or poor prognosis. However, the rate of pts with partial response to N+I (32%) is lower of that reported with the combination of axitinib plus pembrolizumab (51%). Moreover, analysis of outcome based on the depth of response strongly suggests a connection between response and survival. This study aims at investigating the efficacy of an intensified strategy with axitinib added to nivolumab in mRCC pts without complete response at the end of N+I induction. Methods: AxIn study (NCT05817903) is a randomized, open-label, multicenter, phase 2 trial evaluating in mRCC pts who completed induction with N+I without complete response or progressive disease, whether the intensification of therapy by adding axitinib to the standard nivolumab can increase the response rate and improve the survival compared to nivolumab alone. Eligible pts with partial response or stable disease after completion of N+I induction as first-line therapy, without any toxicity ≥ G2, and candidates to maintenance nivolumab as per standard clinical practice will be randomized 1:1 to intensification of therapy with axitinib in addition to nivolumab (Arm A) or nivolumab alone (Arm B). The primary endpoint is to assess the ORR of pts treated with the intensification of axitinib plus nivolumab compared to the standard of care of nivolumab monotherapy. Secondary endpoints include PFS, OS, depth of response, duration of response, quality of life, and safety. Exploratory biomarkers analysis will be performed. The trial is actively recruiting. Clinical trial information: NCT05817903 .
Improving health education through a patient-clinician partnered intervention in the patient with genitourinary cancer.
Authors: Parker Jessica
Published: January 2024

TPS525

Background: Health literacy is associated with health equity, acts as a cornerstone in optimizing patient care and is associated with improved quality of life. The objective of this project is to improve health literacy in patients with genitourinary cancer through a patient-clinician partnered education intervention. Synthesis of Literature Utilization of a targeted education program delivered in-person using voice instruction demonstrated the greatest significant effect on health-related quality of life; the additional of illustration and text further improved this metric. Optimal health related quality of life is associated with greater comprehension of disease and adherence to treatment plan, heightened self-efficacy, and improvement in patient-provider communication. Methods: The intervention is a patient-clinician partnered written form used in conjunction with verbal instruction. The patient documents reasons for the visit and primary concerns to be addressed prior to the provider encounter during the visit. The Action Plan then records the treatment plan and next steps discussed during the visit. A Confidence Ruler acts as a visual representation of patient confidence in the plan of care, acting as a prompt to the provider to ensure adequate information transfer at conclusion of the visit. The patient then retains the written form highlighting the care discussion for reference and recall as needed. Evaluation A five-point Likert test will measure change pre/post intervention; data will be analyzed in a cohort looking at improvement in overall mean. The HRQOL-14 and the CHLT-6 modified will be used to assess baseline health related quality of life and health literacy respectively followed by cohort analysis of the means to determine efficacy outcomes. The primary outcome is to improve health literacy in all patients within a genitourinary oncology clinic population using is a written tool in concurrence with verbal instruction with secondary focus on improving health-related quality of life in the same population. Recommendation Health literacy must be assessed each visit to optimize patient care outcomes and quality of life. Targeted health education must be patient specific and titrated to individual health literacy needs.
“The Bathed Ones”: Transformation into Gods among the Precontact Nahua
Authors: Madajczak Julia
Published: January 2024

In the sixteenth century, Fray Diego Durán gave rise to a scholarly myth that the primary purpose of Nahua ritual baths was “purification.” This article deconstructs his interpretation, focusing on baths performed on deities’ impersonators (ixiptla), and particularly the so-called tlaaltiltin, “bathed ones.” It argues that “baths,” which often consisted of merely sprinkling one’s face with water, had, above all, a transformative power. In the case of deities’ impersonators, they helped them change their ontological status, converting humans into gods and, sometimes, the other way around. The article concludes that the fabrication of a deity’s ixiptla necessarily involved applying a special kind of liquid, different for every god. Like godly attires, these “waters” contained the god’s traits or essence that enabled the transformation.
Asset-Based Microfinance for Microenterprises: Evidence from Pakistan
Authors: Bari Faisal , Malik Kashif , Meki Muhammad , Quinn Simon
Published: January 2024

We run a field experiment offering graduated microcredit clients the opportunity to finance a business asset worth four times their usual borrowing limit. We implement this using a hire-purchase contract; our control group is offered a zero interest loan at the usual borrowing limit. We find large, significant, and persistent effects: treated microenterprise owners run larger businesses with higher profits; consequently, household consumption increases, particularly on food and children’s education. A dynamic structural model with nonconvex capital adjustment costs rationalizes our results and allows counterfactual analysis; this highlights the potential for welfare improvements through large capital injections that are financially sustainable. (JEL C93, D22, G21, G32, L25, O14, O16)
A decade of corporate governance in Brazil: 2010-2019
Authors: Black Bernard , Carvalho Antonio Gledson , Gallucci Netto Humberto
Published: January 2024

We take advantage of the Brazilian mandatory corporate governance (CG) reporting system to build an overall Brazil Corporate Governance Index (BCGI) and subindices (CGIs), and track changes in firms' scores over the 10-year period from 2010-2019. We show that overall CG level improved significantly between 2010 and 2019, with most of the improvement over the first part of this period. The improvement has two sources: an increase in the proportion of high-standard listings (Novo Mercado and Level 2, NML2) versus low-standard listings (Level 1 and regular, L1R), and within-firm improvement in CG practices. In the first half of the sample period, both NML2 and L1R firms improved CG practices considerably. Overall improvement in the second half of the sample period reflects an increasing proportion of NML2 firms, plus gradual improvement in L1R CG levels; with nearly constant NML2 levels. Improvements were stronger for Board Procedure and Disclosure subindices. Firms in both listings improved their CG. Overall improvement was stronger in NML2 than in L1R, but was concentrated in the period from 2010-2015.
Le concept de matrice dans L'Art de la Fugue de Johann Sebastian Bach
Authors: Αλεβίζος Κωνσταντίνος
Published: January 2024

Στόχος της διατριβής είναι να καταδείξει ότι όλες οι συνθέσεις που περιέχονται στην "Τέχνη της Φούγκας" συνδέονται μεταξύ τους από ένα μοτίβο στενών και ουσιαστικών δεσμών, οι οποίοι υπερβαίνουν μια απλή συνύπαρξη ή επεξεργασία ενός κοινού θέματος: αποτελούν μια ενότητα και είναι διατεταγμένες σε μια ακολουθία αυξανόμενης τεχνικής. Ο συγγραφέας προβαίνει σε λεπτομερή ανάλυση όλων των φουγκών σε τρία επίπεδα, τον ρυθμό, την αρμονία και την αρμονία. Μορφολογία- προσδιορίζει και ταξινομεί όλα τα στοιχεία που δημιουργούν την ενότητα: παρουσιάζει τη μέθοδο και τη σουίτα των τέλος, προτείνει νέα αναλυτικά εργαλεία για την κατανόηση της Φούγκας. των κύριων ζητημάτων που σχετίζονται με το έργο, τη σειρά των φούγκων και την επιδιωκόμενη από τον συνθέτη επιλογή των μουσικών οργάνων.
Logic-Based Benders decomposition for transportation and manufacturing problems
Authors: Αυγερινός Ιωάννης
Published: January 2024

Η παρούσα διατριβή εξετάζει την "Αποσύνθεση Logic-Based Benders'', μια σύγχρονη μέθοδο διαχωρισμού, προερχόμενη από την κλασσική Αποσύνθεση Benders. Καθώς ένα μεγάλης κλίμακας πρόβλημα βελτιστοποίησης δεν μπορεί να επιλυθεί απευθείας με τις τυπικές μεθόδους ακριβείας, είναι εύλογος ο διαχωρισμός του σε δύο υπομέρη, καθένα από τα οποία μπορεί να λυθεί βέλτιστα πιο εύκολα. Τα δύο υπομέρη ανταλλάσσουν γνώση επαναληπτικά, χρησιμοποιώντας γραμμικές ανισότητες που ονομάζονται ``Τομές Benders''. Η ευελιξία της μεθόδου μας επιτρέπει να διαχειριζόμαστε περίπλοκα προβλήματα μεγάλης κλίμακας, προερχόμενα από πραγματικά περιβάλλοντα μεταφοράς και βιομηχανίας. Με αφορμή τέτοιες περιπτώσεις, δείχνουμε διαφορετικές προσεγγίσεις της μεθόδου για να υπολογίσουμε σχεδόν βέλτιστες λύσεις σε εύλογο χρόνο για προβλήματα βιομηχανικής κλίμακας, δηλαδή για εκατοντάδες παραγγελίες προς παραγωγή ή παράδοση. Πέρα από την πρακτική συνεισφορά της διατριβής, που αποτελείται από τη συγκέντρωση αποδοτικών σχημάτων LBBD για τα υπό εξέταση προβλήματα, η τεχνική συνεισφορά αφορά τη δημιουργία έγκυρων και ισχυρών τομών Benders, που μπορούν να χρησιμοποιηθούν για γενικευμένες κατηγορίες προβλημάτων βελτιστοποίησης. Οι περιπτώσεις αυτές αφορούν προβλήματα ακέραιων μη δυαδικών μεταβλητών ή την απαλοιφή γειτονιών πολλαπλών λύσεων με χρήση μίας τομής, χωρίς απώλεια της βελτιστότητας. Κυριάρχο θέμα της διατριβής αποτελεί η εφαρμοσιμότητα της μεθόδου, όπως απδεικνύεται από την επιτυχημένη εφαρμογή της στα προβλήματα που παρουσιάζονται. Βασικό θέμα συζήτησης αποτελεί επίσης η περιγραφή του θεωρητικού υποβάθρου και της ανάπτυξης της μεθόδου κατά τις τελευταίες δεκαετίες, ξεκινώντας από τις βασικές αρχές του Ακέραιου Προγραμματισμού και καταλήγοντας στη σύγχρονη συναφή βιβλιογραφία. Τέλος, αναδεικνύονται υποσχόμενες προεκτάσεις, όπως η αξιοποίηση της μεθόδου για τη γραμμικοποίηση μη-γραμμικών προβλημάτων ή ως μηχανισμός επίλυσης στοχαστικών προβλημάτων, ως προοπτικές για μελλοντική έρευνα.
Macro-economic determinants of the IPO waves: An assessment of G-7 countries
Authors: ÖZYEŞİL MUSTAFA , Benhür Aktürk Esin
Published: January 2024

Background The objective of this study is to explore the macroeconomic factors considered by companies in scheduling initial public offerings (IPOs). Methods The panel data analysis method was employed to investigate the relationship between the frequency of IPOs and selected macroeconomic indicators within the stock markets of G-7 countries spanning from 1999 to 2020. An econometric model utilizing a random effect approach was utilized, employing the Driscoll-Kraay resistant standard estimator to address deviations. Results The analysis revealed that stock market returns exert a statistically significant positive influence on the volume of public offerings. Conclusions Based on these findings, it can be inferred that companies strategically time their IPOs during periods characterized by relatively high stock market returns.
Until the dawn: everyday experiences of people living with COVID-19 during the pandemic in Thailand
Authors: Imkome Ek-uma , Moonchai Kamonchanok
Published: January 2024

Background This study aims to understand and analyze the complex experiences of people living with COVID-19 to support future cases. Methods Purposive and snowball sampling techniques were employed to collect data through in-depth interviews; the data were combined with non-aggregated behavioral observations. The lived experiences of 15 individuals were collected through semi-structured interviews and analyzed using a phenomenological-hermeneutic approach. We used the thematic analysis technique to analyze the data. The COREQ guidelines for reporting qualitative studies were performed. Results Through analysis, themes of stress, economic impact, social stigma, social support, and unexpected benefits were identified. Participants further expressed economic and social concerns during the interviews. Conclusion The identified themes can help develop multidisciplinary treatment strategies that would be useful during a healthcare crisis, establish comprehensive support systems that could address economic and social problems, and provide training for employees for post-COVID-19 assistance.
Validation of the Dominican system for measuring early childhood development
Authors: Sánchez-Vincitore Laura V. , Alonso Pellerano María Angélica , Valdez María Elena , Jiménez Angie Sabrina , Ruiz-Matuk Carlos B , Castro Arachu , Díaz Felipe , Cubilla-Bonnetier Daniel
Published: January 2024

Background The purpose of the study was to determine the psychometric properties of the Dominican System for Measuring Early Childhood Development (SIMEDID, for its Spanish acronym), to adjust the sequence of item presentation, and to provide age-standardized norms for each item, to enable policy and program managers to make decisions based on specific and structured data. Methods After approval from an ethics committee, a total of 948 children from 0 to 60 months participated in this study. Participants were evaluated on four early childhood development domains (gross motor, fine motor, language development, and socio-emotional development). The data were collected from November 2021 to February 2022, either at early childhood care centers or at home, using mobile devices that guided the evaluators through the screener. Data were later synced to a global database. Psychometric properties were calculated using Cronbach’s alpha and split-half parallel reliability. For reorganizing item presentation and to obtain age-standardized norms, we conducted a logistic regression analysis for each item on dependent variable item success, and independent variable age. Results The instrument showed excellent reliability and additional evidence of validity. The item presentation order was rearranged according to the probability of item success progression. In addition, the study characterized the expected evolution of item success probability across participants’ age. Conclusions SIMEDID is a valid and reliable instrument for depicting childhood development in national evaluations. Its integration with electronic platforms for national monitoring represents a cost-effective, time-efficient screening tool adapted to the Dominican sociocultural context. This represents a promising tool to strengthen strategies that support early childhood development.
REQUIREMENTS FOR THE INNOVATIVE INFRASTRUCTURE TO ENSURE TECHNOLOGICAL SUPERIORITY OF THE RUSSIAN ECONOMY
Authors: Galimova Margarita P.
Published: January 2024

Addressing the challenge of ensuring a technological breakthrough in the Russian economy by generating and commercializing indigenous technologies under conditions of sanctions pressure is a pressing task that can be solved based on accelerating innovation development in industry, including the manufacturing sector that provides the means of production for all types of economic activities. An innovative infrastructure is called upon to create a motivating and favorable environment for the realization of full innovation cycles, commercialization, scaling, and diffusion of innovations, which at the present stage does not meet the demands of consumer-innovators and generates technological backwardness. The need for transformation of the innovation infrastructure has become apparent.

To determine the directions of transformation, it is proposed to apply a client-oriented approach, which shifts management emphases from optimizing internal processes to optimizing solutions for consumer problems.

The article utilizes elements of the quality structuring method, namely, identifying consumer requests and analyzing the compliance of innovative infrastructure elements with requirements. Based on the analysis, directions for transformation are formulated, with subsequent ranking and evaluation of effectiveness.

Purpose. The objective is to identify and structure the requirements for an innovative infrastructure that ensures national technological superiority, based on a client-oriented approach in the context of transitioning to a digital economy and geopolitical instability.

Methodology in article: The article employs a general scientific method of analysis and synthesis, as well as a method of descriptive literature review. To present the results of the research, a tabular method is applied. The methodological foundation of the study is the client-oriented approach.

Results: The requirements of consumers to the innovative infrastructure have been identified and structured, enabling the creation and maintenance of an effective innovative environment for the growth of innovative and technological activities of industrial enterprises as a key condition for ensuring technological superiority under destructive sanction pressures.

Practical implications: The obtained results are advisable to be applied in the development of innovative strategies and in justifying the choice of innovative infrastructure objects for addressing technological breakthrough challenges.
Ciclos de mejora en el aula. Curso 2022-23 Experiencias de Innovación Docente de la Universidad de Sevilla
Authors: Porlán Rafael , Villarejo Ramos Ángel Francisco
Published: January 2024

La Universidad de Sevilla, en su compromiso con la mejora continua de la docencia, viene poniendo en marcha periódicamente el Programa de Formación, Innovación e Investigación Docente del Profesorado (Programa FIDOP) en el marco de su Plan Propio de Docencia. Dicho programa tiene por objetivo una formación e innovación orientada por un modelo docente centrado en el aprendizaje activo del estudiantado, como recomiendan los organismos internacionales relacionados con la Educación Superior. La filosofía y los principios básicos del Programa FIDOP pretenden generar un proceso de cambio conceptual y metodológico que acerque al Personal Docente e Investigador (PDI) de la Universidad de Sevilla -tanto al experimentado como al que inicia su carrera docente- a un modelo docente más acorde con las evidencias emanadas de las investigaciones que se han venido desarrollando en los últimos años sobre Educación Superior, Didáctica de las diversas Disciplinas, Psicología del Aprendizaje, Epistemología, Neurociencia, etc. En este marco, los participantes en el programa realizan anualmente Ciclos de Mejora en el Aula (CIMA) que van sustituyendo gradualmente las clases más convencionales por experiencias con una participación activa de los estudiantes, en línea con lo expuesto anteriormente, siempre con el objetivo de mejorar asignaturas completas. Se presenta en este monográfico, a modo de capítulos, una parte de los CIMA experimentados durante el curso 2022/23, previamente sometidos a evaluación por pares por el equipo de formadores y dinamizadores del programa. Con el objetivo de aportar un conocimiento docente útil para otros colegas, el índice está organizado por especialidades y los capítulos presentan una estructura básica común con los siguientes apartados: diseño previo del CIMA (abarcando los contenidos, el modelo metodológico, la secuencia de actividades y la evaluación), el desarrollo real de las sesiones, la evaluación del aprendizaje final alcanzado por el alumnado, la evaluación crítica de la experiencia y los principios didácticos orientadores para la mejora de futuros CIMAs.
Guerra en la zona gris y conflicto étnico
Authors: Belo Dani , Carment David
Published: January 2024

Aunque el panorama internacional contemporáneo está dominado por guerras intrastatales, las relaciones internacionales difícilmente pueden considerarse pacíficas. En otras palabras, los Estados continúan participando en conflictos, pero por debajo del umbral de la guerra abierta. El artículo examina las tendencias generales y las consecuencias que el conflicto étnico tiene para la guerra futura, ya que los Estados emplean tácticas híbridas y estrategias de la zona gris para apoyar a sus parientes étnicos. Muchos de los conflictos étnicos actuales pueden describirse como secesionistas, en los cuales Estados externos y otros actores internacionales se ven involucrados en un conflicto, o irredentistas, en los cuales dos o más estados entran en guerra por una reclamación irredentista. El uso de tales conflictos étnicos por parte de interventores externos para participar en conflictos en la zona gris se está convirtiendo en una norma en los asuntos internacionales. El texto se centra en los casos de las intervenciones en la zona gris de Rusia en Georgia, Ucrania y la región Báltica, y se contrastan con los casos de Azerbaiyán-Armenia, el Sáhara Occidental, así como Etiopía-Eritrea, para mostrar tanto la continuidad como la transformación en la guerra. Se cierra identificando algunas de las razones por las cuales hay variación en estos casos y las implicaciones que esto tiene para la gestión de conflictos y el futuro de la guerra.
Digital Approaches to Societal Grand Challenges: Toward a Broader Research Agenda on Managing Global-Local Design Tensions
Authors: Nambisan Satish , George Gerard
Published: January 2024

Policy/Practice-Focused Abstract

Despite considerable and continued resource investments, effective solutions to broad-scope problems of social interest or societal grand challenges (GCs) have proven to be elusive in many domains. In multiactor situations that characterize GCs, divergent goals, needs, priorities, and capabilities of global and local actors create organizing design tensions that need to be considered before solutions can be enacted. Emergent digital technologies can play an important and transformative role in addressing the organizing design tensions that pervade such collective action problems. In this article, we draw on Elinor Ostrom’s principles of public value creation and identify a set of eight organizing design tensions that arise from employing global and local perspectives in addressing GCs. We consider novel digital approaches—that involve alternative arrangements of digital and socio-political elements in GC settings—to resolving each of these design tensions. Our discussion foreshadows the considerable opportunity for information systems research to contribute to the broader dialog on GCs; inform GC-related policy and practice at global and local levels; and, more broadly, speed the identification and enactment of effective solutions to grand challenges.
Joint Mixability and Notions of Negative Dependence
Authors: Koike Takaaki , Lin Liyuan , Wang Ruodu
Published: January 2024

A joint mix (JM) is a random vector with a constant component-wise sum. The dependence structure of a joint mix minimizes some common objectives, such as the variance of the component-wise sum, and it is regarded as a concept of extremal negative dependence. In this paper, we explore the connection between the joint mix structure and popular notions of negative dependence in statistics, such as negative correlation dependence, negative orthant dependence, and negative association. A joint mix is not always negatively dependent in any of these senses, but some natural classes of joint mixes are. We derive various necessary and sufficient conditions for a joint mix to be negatively dependent and study the compatibility of these notions. For identical marginal distributions, we show that a negatively dependent joint mix solves a multimarginal optimal transport problem for quadratic cost under a novel setting of uncertainty. Analysis of this optimal transport problem with heterogeneous marginals reveals a trade-off between negative dependence and the joint mix structure.

Funding: T. Koike was supported by the Japan Society for the Promotion of Science [Grant JSPS KAKENHI JP21K13275]. R. Wang acknowledges financial support from the Natural Sciences and Engineering Research Council of Canada [Grants RGPIN-2018-03823 and RGPAS-2018-522590].
The need for urgent intervention as premature deaths from cardiovascular disease reach an all-time high
Authors: Hashimi Samina
Published: January 2024

Samina Hashimi, assistant editor of the British Journal of Cardiac Nursing, discusses the implications of concerning new data from the British Heart Foundation, highlighting the record number of deaths from cardiovascular disease and the need for urgent action.
Lipoarabinomannan-based tuberculosis diagnosis using a fiber cavity ring down biosensor
Authors: Ullah Ubaid , Saleem Seerat , Farooq Muddassar , Yameen Basit , Imran Cheema M.
Published: January 2024

Despite existing for millennia, tuberculosis (TB) remains a persistent
global health challenge. A significant obstacle in controlling TB
spread is the need for a rapid, portable, sensitive, and accurate
diagnostic test. Currently, sputum culture stands as a benchmark test
for TB diagnosis. Although highly reliable, it necessitates advanced
laboratory facilities and involves considerable testing time. In this
context, we present a rapid, portable, and cost-effective optical
fiber sensor designed to measure lipoarabinomannan (LAM), a TB
biomarker found in patients’ urine samples. Our sensing
approach is based on the applications of phase shift-cavity ringdown
spectroscopy (PS-CRDS) to an optical fiber cavity created by two fiber
Bragg gratings. A tapered fiber is spliced inside the optical cavity
to serve as the sensing head. We functionalize the tapered fiber
surface with anti-LAM antigen CS-35 through a unique chemistry,
creating a strong affinity for LAM molecules. We measure the phase
difference between the cavity transmission and the reference
modulating signal at the cavity output. The measured phase is directly
proportional to the injected LAM concentrations in aqueous solutions
over the sensing head. Our demonstrated sensor provides a detection
limit of 10 pg/mL and a sensitivity of 0.026°/pg/mL. This
sensor holds promise for numerous applications in the healthcare
sector, particularly in low-resource settings.
3D drift correction for super-resolution imaging with a single laser light
Authors: Li Yiming , Li Yunze , He Yingchuan , Fang Ke , Zhou Lulu , Wang Zhen , Shi Wei
Published: January 2024

Single-molecule localization microscopy (SMLM) enables three-dimensional (3D) super-resolution imaging of nanoscale structures within biological samples. However, prolonged acquisition introduces drift between the sample and the imaging system, resulting in artifacts in the reconstructed super-resolution image. Here, we present a novel 3D drift correction method that utilizes both the reflected and scattered light from the sample. Our method employs the reflected light of a near-infrared (NIR) laser for focus stabilization while synchronously capturing speckle images to estimate lateral drift. This approach combines high-precision active compensation in the axial direction with lateral post-processing compensation, achieving the abilities of the 3D drift correction with a single laser light. Compared to the popular localization events-based cross-correlation method, our approach is much more robust, especially for datasets with sparse localization points.
Vision-based collective motion: A locust-inspired reductionist model
Authors: Krongauz David L. , Ayali Amir , Kaminka Gal A.
Published: January 2024

Naturally occurring collective motion is a fascinating phenomenon in which swarming individuals aggregate and coordinate their motion. Many theoretical models of swarming assume idealized, perfect perceptual capabilities, and ignore the underlying perception processes, particularly for agents relying on visual perception. Specifically, biological vision in many swarming animals, such as locusts, utilizes monocular non-stereoscopic vision, which prevents perfect acquisition of distances and velocities. Moreover, swarming peers can visually occlude each other, further introducing estimation errors. In this study, we explore necessary conditions for the emergence of ordered collective motion under restricted conditions, using non-stereoscopic, monocular vision. We present a model of vision-based collective motion for locust-like agents: elongated shape, omni-directional visual sensor parallel to the horizontal plane, and lacking stereoscopic depth perception. The model addresses (i) the non-stereoscopic estimation of distance and velocity, (ii) the presence of occlusions in the visual field. We consider and compare three strategies that an agent may use to interpret partially-occluded visual information at the cost of the computational complexity required for the visual perception processes. Computer-simulated experiments conducted in various geometrical environments (toroidal, corridor, and ring-shaped arenas) demonstrate that the models can result in an ordered or near-ordered state. At the same time, they differ in the rate at which order is achieved. Moreover, the results are sensitive to the elongation of the agents. Experiments in geometrically constrained environments reveal differences between the models and elucidate possible tradeoffs in using them to control swarming agents. These suggest avenues for further study in biology and robotics.
Understanding the perspectives and needs of multiple stakeholders: Identifying key elements of a digital health intervention to protect against environmental hazards
Authors: Workman Annabelle , Campbell Sharon L. , Williamson Grant J. , Lucani Chris , Bowman David M. J. S. , Cooling Nick , Johnston Fay H. , Jones Penelope J.
Published: January 2024

AirRater is a free environmental health smartphone app developed and available in Australia that collects individual health data and disseminates environmental hazard information to populations. Following previous evaluations with app users, the aim of this study was to better understand how clinicians, government agency and non-government advocacy group representatives perceive an app designed to reduce the impacts of environmental hazards on individual and public health. Nine government agency and non-government advocacy group representatives, along with 11 clinicians based in Australia participated in a semi-structured interview or focus group to explore perspectives on AirRater. Interview and focus group data were transcribed and analysed using the qualitative data analysis software NVivo. Results indicate that for clinicians, apps like AirRater can add value as an educational, patient self-management and diagnostic tool. For government and peak bodies, apps can add value by addressing environmental health literacy and monitoring and forecasting gaps, as well as supporting advocacy efforts and public health surveillance. We conclude that environmental health smartphone apps can support a range of stakeholders to achieve shared goals and priorities related to individual and public health outcomes. Further research is needed to better understand how apps could be embedded into clinical practice and policy settings.
Influence of spatial structure migration of overlying strata on water storage of underground reservoir in coal mine
Authors: Cao Zhiguo , Jing Suolin , Wang Lujun , Meng Fanbao , Han Yanning
Published: January 2024

Underground reservoir technology for coal mines can realize the coordinated development of coal exploitation and water protection in water-shortage-prone areas. The seepage effect of the floor seriously affects the safety of underground reservoirs under the action of mining damage and seepage pressure. Focusing on the problem of floor seepage in underground reservoirs, a spatial mechanical model of underground reservoirs was established. The main factors affecting the seepage of the surrounding rock were studied. The seepage pressure law in different stages of spatial structure evolution of overlying strata was explored. The results showed that pressure change was the main factor affecting the stability of a reservoir’s surrounding rock. The pore space between the broken and fractured rock in the water-flowing fractured zone was the main water storage space, which was directly related to the development of a breaking arch. According to the spatial structure evolution process of the overlying strata, the water storage state of an underground reservoir was divided into two stages and three situations. The seepage pressure was mainly affected by the water pressure and the overlying strata weight. The water pressure was affected by the reservoir head height, and the overlying strata weight was mainly affected by the overlying strata thickness.
Introducing exceptional growth mining—Analyzing the impact of soil characteristics on on-farm crop growth and yield variability
Authors: Mulders Puck J. A. M. , van den Heuvel Edwin R. , Reidsma Pytrik , Duivesteijn Wouter
Published: January 2024

Sustainable intensification of agriculture requires understanding of the effect of soil characteristics and nutrient supply on crop growth. As farms are increasing in size by acquiring small fields from various farmers, the soil characteristics and nutrient supply might be very different from field to field, while at the same time specific soil properties might limit the nutrient uptake. As a result, there might be a large number of heterogeneous reasons why crop growth varies significantly. New data analysis techniques can help to explain variability in crop growth among fields. This paper introduces Exceptional Growth Mining (EGM) as a first contribution. EGM instantiates the data mining framework Exceptional Model Mining (EMM) such that subgroups of fields can be found that grow exceptionally in terms of three growth parameters (high/low maximum growth, steep/flat linear growth and early/late midpoint of maximum growth). As second contribution, we apply EGM to a case study by analyzing the dataset of a potato farm in the south of the Netherlands. EGM consists of (i) estimating growth curves by applying nonlinear mixed models, (ii) investigating the correlation between the estimated growth parameters, and (iii) applying EMM on these growth curve parameters using a growth curve-specific quality measure. By applying EGM on the data of the potato farm, we obtain the following results: 1) the estimated growth curves represent the variability in potato tuber growth very well (R2 of 0.92), 2) the steepness of the growth curve has a strong correlation with the maximum growth and the midpoint of maximum growth, and the correlation between the midpoint of maximum growth and maximum growth is weak, 3) the subgroup analyses indicate that: high values of K correspond to high maxima; low values of K correspond to low maxima, steep growth curves’, and a late midpoint of halfway growth; Mg influences the midpoint of the growth curve; values of B are higher on dry soils with high tuber growth, while low values of B are found on wet soils with high tuber growth; high values of Zn, Mn, and Fe are found in subgroups with low tuber weight, probably related to the soil’s low pH. In summary, this paper introduces EGM to obtain understanding in crop response to soil properties and nutrient supply. In addition, EGM provides a way to analyze only small parts of a large dataset, such that the impact of soil factors on growth can be analyzed on a more detailed level than existing methods.
Numerical stability of DeepGOPlus inference
Authors: Gonzalez Pepe Inés , Chatelain Yohan , Kiar Gregory , Glatard Tristan
Published: January 2024

Convolutional neural networks (CNNs) are currently among the most widely-used deep neural network (DNN) architectures available and achieve state-of-the-art performance for many problems. Originally applied to computer vision tasks, CNNs work well with any data with a spatial relationship, besides images, and have been applied to different fields. However, recent works have highlighted numerical stability challenges in DNNs, which also relates to their known sensitivity to noise injection. These challenges can jeopardise their performance and reliability. This paper investigates DeepGOPlus, a CNN that predicts protein function. DeepGOPlus has achieved state-of-the-art performance and can successfully take advantage and annotate the abounding protein sequences emerging in proteomics. We determine the numerical stability of the model’s inference stage by quantifying the numerical uncertainty resulting from perturbations of the underlying floating-point data. In addition, we explore the opportunity to use reduced-precision floating point formats for DeepGOPlus inference, to reduce memory consumption and latency. This is achieved by instrumenting DeepGOPlus’ execution using Monte Carlo Arithmetic, a technique that experimentally quantifies floating point operation errors and VPREC, a tool that emulates results with customizable floating point precision formats. Focus is placed on the inference stage as it is the primary deliverable of the DeepGOPlus model, widely applicable across different environments. All in all, our results show that although the DeepGOPlus CNN is very stable numerically, it can only be selectively implemented with lower-precision floating-point formats. We conclude that predictions obtained from the pre-trained DeepGOPlus model are very reliable numerically, and use existing floating-point formats efficiently.
Leader–follower formation control based on non-inertial frames for non–holonomic mobile robots
Authors: Velasco–Villa M. , Rodriguez–Angeles A. , Maruri–López I. Z. , Báez-Hernández J. A. , Cruz Morales R. D.
Published: January 2024

A chain formation strategy based on mobile frames for a set ofndifferential drive mobile robots is presented. Considering two consecutive robots in the formation, robotsRiandRi+1. It is intended that robotRi+1follows the delayed trajectory,τunits of time, of the leader robotRi. In this way, the follower robotRi+1becomes the leader robot for robotRi+ 2in the formation and so on. With this formation policy, the trailing distance between two consecutive robots varies accordingly to the velocity of theRileader robot. Mobile frames are located on the body of the vehicles, in such a way that the position of robotRiis determined with respect to the frame located onRi+1robot. The strategy relies on the fact that the general leader robotR1describes any trajectory generated by bounded linearv1(t) and angularω1(t) velocities. For the remaining vehicles in the string, the strategy considers a desired trajectory for the follower robotRi+1obtained by an estimation of the delayed trajectory of the leader robotRi. This desired estimated trajectory is obtained under the knowledge of the actual and past input velocities of theRirobot. To formally prove the convergence of the formation strategy, the equations describing the time variation of the relative posture between any pair of consecutive vehicles in the formation are obtained, and a feedback law based on local measurements is proposed to get the convergence of robotRi+1to the delayed trajectory,τunits of time, of the trajectory previously described by robotRi. Lyapunov techniques are considered for this fact. The effectiveness of the chain formation solution is evaluated by means of numerical simulations and real time experiments showing an adequate convergence.
Update on the Study of Alzheimer´s Disease Through Artificial Intelligence Techniques
Authors: Garea-Llano Eduardo
Published: January 2024

Alzheimer's disease is the most common form of dementia that can cause a brain neurological disorder with progressive memory loss as a result of brain cell damage. Prevention and treatment of disease is a key challenge in today's aging society. Accurate diagnosis of Alzheimer's disease plays an important role in patient management, especially in the early stages of the disease, because awareness of risk allows patients to undergo preventive measures even before brain damage occurs irreversible.
Over the years, techniques such as statistical modeling or machine learning algorithms have been used to improve understanding of this condition. The objective of the work is the study of the methods of detection and progression of Alzheimer's disease through artificial intelligence techniques that have been proposed in the last three years.
New Model of Photovoltaic System Adapted by a Digital MPPT Control and Radiation Predictions Using Deep Learning
Authors: Zouhri Amal , El Mallahi Mostafa
Published: January 2024

Forecasting solar radiation is one of the most useful impacts that can give us a deep vision on maintaining the integrity of solar systems. The availability and ease of use of the data make this process simpler. Predictions may be produced using various data sources. In fact, there are two different forms that can be identified. The first one was the use of historical solar radiation data, while the second one was the use of other meteorological parameters. The availability and choice of the data source can have an effect on the choice of the model and methods used. Our proposed article aims to take research as an example to review the solar radiation situation in Morocco and outline the methods of predicting solar radiation using different machine learning and deep learning methods like ANN, MLP, BPNN, DNN, and LSTM, which are used in different regions in Morocco.
Heavy Moving Average Distances in Sales Forecasting
Authors: Olazabal-Lugo Maricruz , Espinoza-Audelo Luis F. , León-Castro Ernesto , Perez-Arellano Luis A. , Blanco-Mesa Fabio
Published: January 2024

This paper presents a new aggregation operator technique that uses the ordered weighted average (OWA), heavy aggregation operators, Hamming distance, and moving averages. This approach is called heavy ordered weighted moving average distance (HOWMAD). The main advantage of this operator is that it can use the characteristics of the HOWMA operator to under-or overestimate the results according to the expectations and the knowledge of the future scenarios, analyze the historical data of the moving average, and compare the different alternatives with the ideal results of the distance measures. Some of the main families and specific cases using generalized and quasi-arithmetic means are presented, such as the generalized heavy moving average distance and a generalized HOWMAD. This study develops an application of this operator in forecasting the sales growth rate for a commercial company. We find that it is possible to determine whether the company's objectives can be achieved or must be reevaluated in response to the actual situation and future expectations of the enterprise.
Application of the Spherical Fuzzy DEMATEL Model for Assessing the Drone Apps Issues
Authors: Pandey Mamta , Litoriya Ratnesh , Pandey Prateek
Published: January 2024

During the past few years, the number of drones (unmanned aerial vehicles, or UAVs) manufactured and purchased has risen dramatically. It is predicted that it will continue to spread, making its use inevitable in all walks of life. Drone apps are therefore expected to overrun the app stores in the near future. The UAV's software is not being studied/researched despite several active research and studies being carried out in the UAV's hardware field. A large-scale empirical analysis of Google Play Store Platform apps connected to drones is being done in this direction. There are, however, a number of challenges with drone apps because of the lack of formal and specialised app development procedures. In this paper, eleven drone app issues have been identified. Then we applied the DEMATEL (Decision Making Trial and Evaluation Laboratory) method to analyse the drone app issues (DIs) and divide these issues into cause and effect groups. First, multiple experts assess the direct relationships between influential issues in drone apps. The evaluation results are presented in spherical fuzzy numbers (SFN). Secondly, convert the linguistic terms into SFN. Thirdly, based on DEMATEL, the cause-effect classifications of issues are obtained. Finally, the issues in the cause category are identified as DI’s in drone apps. The outcome of the research is compared with the other variants of DEMATEL like rough‐Z‐number‐based DEMATEL and spherical fuzzy number, and the comparative results suggest that Spherical Fuzzy-DEMATEL is the most fitting method to analyse the interrelationship of different issues in drone apps. The outcome of this work definitely assists the software industry in the successful identification of the critical issues where professionals and project managers could really focus.