bluuebunny/crossref_metadata_2025 huggingface dataset:
Challenges with segmenting intraoperative ultrasound for brain tumours
Authors: Weld Alistair , Dixon Luke , Anichini Giulio , Patel Neekhil , Nimer Amr , Dyck Michael , O’Neill Kevin , Lim Adrian , Giannarou Stamatia , Camp Sophie
Published: August 2024

Objective - Addressing the challenges that come with identifying and delineating brain tumours in intraoperative ultrasound. Our goal is to both qualitatively and quantitatively assess the interobserver variation, amongst experienced neuro-oncological intraoperative ultrasound users (neurosurgeons and neuroradiologists), in detecting and segmenting brain tumours on ultrasound. We then propose that, due to the inherent challenges of this task, annotation by localisation of the entire tumour mass with a bounding box could serve as an ancillary solution to segmentation for clinical training, encompassing margin uncertainty and the curation of large datasets. Methods - 30 ultrasound images of brain lesions in 30 patients were annotated by 4 annotators - 1 neuroradiologist and 3 neurosurgeons. The annotation variation of the 3 neurosurgeons was first measured, and then the annotations of each neurosurgeon were individually compared to the neuroradiologist’s, which served as a reference standard as their segmentations were further refined by cross-reference to the preoperative magnetic resonance imaging (MRI). The following statistical metrics were used: Intersection Over Union (IoU), Sørensen-Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD). These annotations were then converted into bounding boxes for the same evaluation. Results - There was a moderate level of interobserver variance between the neurosurgeons

$$[IoU:0.789, \ DSC:0.876, \ HD:103.227]$$

[
I
o
U
:
0.789
,

D
S
C
:
0.876
,

H
D
:
103.227
]

and a larger level of variance when compared against the MRI-informed reference standard annotations by the neuroradiologist, mean across annotators

$$[IoU:0.723, \ DSC:0.813, \ HD:115.675]$$

[
I
o
U
:
0.723
,

D
S
C
:
0.813
,

H
D
:
115.675
]

. After converting the segments to bounding boxes, all metrics improve, most significantly, the interquartile range drops by

$$[IoU:37\%, \ DSC:41\%, \ HD:54\%]$$

[
I
o
U
:
37
%
,

D
S
C
:
41
%
,

H
D
:
54
%
]

. Conclusion - This study highlights the current challenges with detecting and defining tumour boundaries in neuro-oncological intraoperative brain ultrasound. We then show that bounding box annotation could serve as a useful complementary approach for both clinical and technical reasons.
Identification of histopathological classification and establishment of prognostic indicators of gastric adenocarcinoma based on deep learning algorithm
Authors: Wang Zhihui , Peng Hui , Wan Jie , Song Anping
Published: August 2024

The aim of this study is to establish a deep learning (DL) model to predict the pathological type of gastric adenocarcinoma cancer based on whole-slide images(WSIs). We downloaded 356 histopathological images of gastric adenocarcinoma (STAD) patients from The Cancer Genome Atlas database and randomly divided them into the training set, validation set and test set (8:1:1). Additionally, 80 H&E-stained WSIs of STAD were collected for external validation. The CLAM tool was used to cut the WSIs and further construct the model by DL algorithm, achieving an accuracy of over 90% in identifying and predicting histopathological subtypes. External validation results demonstrated the model had a certain generalization ability. Moreover, DL features were extracted from the model to further investigate the differences in immune infiltration and patient prognosis between the two subtypes. The DL model can accurately predict the pathological classification of STAD patients, and provide certain reference value for clinical diagnosis. The nomogram combining DL-signature, gene-signature and clinical features can be used as a prognostic classifier for clinical decision-making and treatment.
Empfehlungen der DGINA und DIVI zur Struktur und Ausstattung von Notaufnahmen 2024
Authors: Brod Torben , Bernhard Michael , Blaschke Sabine , Dodt Christoph , Dormann Patrick , Drynda Susanne , Dubb Rolf , Gries André , Hoffmann Florian , Janssens Uwe , Kaltwasser Arnold , Markewitz Andreas , Möckel Martin , Pedersen Vera , Pin Martin , Walcher Felix , Wrede Christian
Published: August 2024

Die Notaufnahmen deutscher Krankenhäuser sind ein zentraler Anlaufpunkt für über 20 Millionen Notfallpatienten pro Jahr. Um eine hochwertige Patientenversorgung sicherstellen zu können, sind personelle, apparative und infrastrukturelle Voraussetzungen erforderlich, die nur bedingt im Beschluss des Gemeinsamen Bundesausschusses (G-BA) zu einem gestuften System von Notfallstrukturen an Krankenhäusern von 2018 festgeschrieben sind. Darüber hinaus gibt es bislang in Deutschland keine einheitlichen Empfehlungen zur erforderlichen Ausstattung von Notaufnahmen. Auf Grundlage existierender Publikationen nationaler und internationaler Fachgesellschaften haben die Deutsche Gesellschaft für Interdisziplinäre Notfall- und Akutmedizin (DGINA) und die Deutsche Interdisziplinäre Vereinigung für Intensiv- und Notfallmedizin (DIVI) Empfehlungen zur Struktur und Ausstattung von Notaufnahmen erarbeitet. Diese umfassen insbesondere Empfehlungen zur ärztlichen und nicht-ärztlichen Personalbesetzung, apparativen und baulichen Ausstattung sowie den für eine effiziente Notfallversorgung erforderlichen Prozessen und Schnittstellen. Weiterhin werden die Aspekte Forschung und Lehre, Qualitätsmanagement und Public Health Surveillance in der klinischen Akut- und Notfallmedizin betrachtet. Mit der Umsetzung dieser Strukturempfehlungen wird eine weitere Professionalisierung der klinischen Akut- und Notfallmedizin in Deutschland angestrebt.
Variation in Zero Plane Displacement and Roughness Length for Momentum Revisited
Authors: Kunadi Ashvath Singh , Silberstein Richard P. , Thompson Sally E.
Published: August 2024

Zero plane displacement height ($$d_0$$

d
0

) and momentum roughness length ($$z_{0m}$$

z

0
m

), describe the aerodynamic characteristics of a vegetated surface. Usually, $$d_0$$

d
0

and $$z_{0m}$$

z

0
m

are assumed to be constant functions of the physical characteristics of the surface. Prior evidence collected from the literature and our examination of flux tower data show that $$d_0$$

d
0

and $$z_{0m}$$

z

0
m

vary in time at sites with tree and shrub canopies, but not grasslands. The conventional explanations of these variations are based on linear functions of wind velocity and friction velocity, with little theoretical basis. This study explains the variation in aerodynamic parameters by matching four analytical canopy velocity models to a logarithmic above-canopy velocity profile at canopy height. $$d_0$$

d
0

and $$z_{0m}$$

z

0
m

come out as functions of 2 non-dimensional terms, the canopy momentum absorption capacity (parameter) and a (measurable) Péclet number. To test the theories of variation, we analysed the velocity profiles from Ozflux and Ameriflux sites. None of the theories could recreate $$d_0$$

d
0

and $$z_{0m}$$

z

0
m

at half-hourly intervals. However, the canopy velocity models were able better to recreate the distribution of the variations in $$d_0$$

d
0

and $$z_{0m}$$

z

0
m

. Additionally, the estimates of canopy momentum absorption capacity varied consistently with phenological changes in the canopies, whereas, the fitting parameters of the linear regression of using wind speed and friction velocity did not exhibit physically interpretable variations. The canopy velocity models may offer better predictions with an accurate estimation of the canopy height, a horizontally homogeneous and rigid canopy, and incorporation of the roughness sublayer.
International Cooperation and Kantian Moral Behaviour: Complements or Substitutes?
Authors: Ulph Alistair , Ulph David
Published: August 2024

Faced with a global emissions problem such as climate change, we know that if countries’ emissions decisions are made in an independent and self-interested fashion the outcome can be very far from optimal. One proposed solution is to have countries enter international environmental agreements (IEAs) whereby individual countries’ emissions decisions are taken in the interests of all the participating countries and so reflect a degree of altruism. However, if the decision to co-operate is made in a self-interested fashion the standard non-cooperative model of IEAs yields the pessimistic conclusion that the more serious the environmental problem the smaller will be the equilibrium membership of an IEA. Our paper examines the implications for emissions, IEA membership and welfare of assuming that countries make both emissions and IEA membership decisions in the alternative moral fashion of acting as imperfect Kantians as defined by Alger and Weibull (Econometrica 81:2269–2302, 2013). We show that (i) the first-best can be achieved when countries either act as Perfect Kantians or by fully cooperating; (ii) in a more imperfect setting, these two forms of moral behaviour are complementary approaches to improving welfare outcomes in the sense that the greater the weights on Kantian behaviour the larger is the equilibrium coalition; (iii) the weights on Kantian behaviour that will induce full cooperation and hence the first-best are significantly less than 1; (iv) for given Kantian weights, our model generates higher equilibrium IEA membership, lower emissions and higher welfare than in the related paper by Eichner and Pethig (International environmental agreements when countries behave morally) which, we argue, does not fully capture the benefits of membership decisions.
Design and Installation of a Local Monitoring System to Validate Debris Flow Methodology for Risk Mitigation
Authors: Moraci Nicola , Ciurleo Mariantonietta , Mandaglio Maria Clorinda , Pisano Marilene
Published: August 2024

Landslides pose significant threats to communities and infrastructure worldwide, necessitating the development of effective hazard and exposure reduction strategies to mitigate the potential risks. In particular, debris flows can be highly destructive landslides. The paper deals with an integrated monitoring system designed both to further validate an existing debris flow inception and propagation methodology developed by the authors and to fine-tune the landslide inception and warning model to be used in an early warning system. The design of the integrated monitoring system, the definition of the acquisition time of instruments, and the processing of the measured data were based on studies performed in the study area of Favazzina (Italy), which is affected by debris flows that are very difficult to monitor. The proposed approach used to design the integrated monitoring system may serve as a useful methodological tool to be adopted in similar geological and geotechnical contexts within the framework of risk mitigation strategies.
Teachers as Creators of Digital Multimedia Learning Materials: Are they Aligned with Multimedia Learning Principles
Authors: Désiron Juliette C. , Schmitz Maria-Luisa , Petko Dominik
Published: August 2024

Digital technologies have facilitated access to instructional multimedia materials, and a large body of literature has shown that these technologies can support students’ learning. However, recent research also shows that many teachers have misconceptions about learning from multimedia materials. Further, numerous studies point out that numerous factors account for the successful use of technologies in class. Based on data from a large-scale study with upper secondary school teachers (n = 2247), we analyzed what predicted teachers’ creation of digital multimedia, to determine whether it was solely technology related factors derived from the will-skill-tool pedagogy model, or also factors related to teachers’ alignment with well-established design and processing principles of multimedia learning. Overall, a third of the respondents were fully aligned with the multimedia principles, and another third with all but the coherence principle. We investigated how this alignment affects the creation of multimedia learning material. Multilevel linear modeling analysis (MLM) indicates that of all multimedia principles, only the dual coding assumption has a significant and positive impact on teachers’ frequency of multimedia document creation. In addition, teachers’ positive beliefs about technology use in class, their self-reported technological knowledge (skill) and their self-reported knowledge in teaching with digital technologies significantly and positively predict how often they create digital multimedia documents. These results stress that, for now, teachers rely more on their technological beliefs and self-reported knowledge to integrate digital tools in their lesson than on their alignment with multimedia design guidelines. As previous studies show that available digital instructional multimedia do not always follow multimedia learning principles, this could lead teachers to create or use inappropriate digital multimedia materials.
Housing the poor? Accessibility and exclusion in the local housing systems of Vienna and Milan
Authors: Wolfgring Constanze , Peverini Marco
Published: August 2024

Despite featuring very different housing systems, both in Vienna and Milan a growing number of people struggle to access affordable and decent housing. Even though social housing policies are in place in both contexts, for many the unregulated and often unaffordable private housing market is the only option. Building upon Antonio Tosi’s work, we centre our analysis on the poor and compare how two very different local housing systems create the conditions for their inclusion or exclusion. Through a comparative analysis of the Viennese and Milanese local housing regimes and adopting a mixed methodology, we discuss how both generate conditions of exclusion and who the ones excluded are, which local policies address the poor and how appropriate these are for mitigating housing exclusion. Finally, we indicate some directions for policies aimed at tackling the intersections of poverty and housing exclusion, advocating for a maximization of the ‘sociality’ of housing policies, involving a shift in prioritisation from the middle classes to the most vulnerable groups and the loosening of certain formal access requirements to housing or welfare services that constitute barriers to these groups, where possible.
Do 5G cell phone towers decrease house prices? Evidence from Warsaw
Authors: Marona Bartłomiej , Gaca Radosław , Głuszak Michał
Published: August 2024

This study investigates the impact of telecommunication infrastructure on residential property prices in Poland. This study contributes to the discussion of economic externalities related to new public infrastructure within the urban landscape. We use hedonic regression, matching techniques, and a difference-in-differences estimator to assess the impact of base transceiver stations on apartment prices in Warsaw, the capital of Poland, which covered market data on the sales of residential premises located in Miasteczko Wilanów estate in Warsaw from 2016 to 2021. In the analysed period, 1,825 residential sales were recorded and used for econometric modelling. The results do not confirm the influence of the vicinity of the wireless communication technology infrastructure on residential real estate prices in the studied local market. In particular, we did not observe a detrimental effect of cell phone towers on housing prices. Additionally, we investigate whether residential sale prices in proximity to BTS changed significantly after the introduction of the 5G standard. This particular issue has not been addressed in the economic literature. We found that the sale prices of apartments located in Warsaw were not statistically affected by the introduction of a fifth-generation technology standard for broadband cellular networks. Our research contributes to a better understanding of stigmatisation effects related to telecommunication infrastructure, and in particular, the links between the presence of cell phone towers and residential property values in the neighbourhood. The results may be of interest to all potential agents involved in neighbourhood conflicts arising from investments in cell phone towers and the development of new communication infrastructure in urban landscapes.
Describing group evolution in temporal data using multi-faceted events
Authors: Failla Andrea , Cazabet Rémy , Rossetti Giulio , Citraro Salvatore
Published: August 2024

Groups—such as clusters of points or communities of nodes—are fundamental when addressing various data mining tasks. In temporal data, the predominant approach for characterizing group evolution has been through the identification of “events”. However, the events usually described in the literature, e.g., shrinks/growths, splits/merges, are often arbitrarily defined, creating a gap between such theoretical/predefined types and real-data group observations. Moving beyond existing taxonomies, we think of events as “archetypes” characterized by a unique combination of quantitative dimensions that we call “facets”. Group dynamics are defined by their position within the facet space, where archetypal events occupy extremities. Thus, rather than enforcing strict event types, our approach can allow for hybrid descriptions of dynamics involving group proximity to multiple archetypes. We apply our framework to evolving groups from several face-to-face interaction datasets, showing it enables richer, more reliable characterization of group dynamics with respect to state-of-the-art methods, especially when the groups are subject to complex relationships. Our approach also offers intuitive solutions to common tasks related to dynamic group analysis, such as choosing an appropriate aggregation scale, quantifying partition stability, and evaluating event quality.
Recovery of cranial nerve neuropathies after LINAC-based stereotactic radiosurgery for benign cavernous sinus meningioma
Authors: Kaisman-Elbaz Tehila , Blumenfeld Philip , Wygoda Marc , Feldman John , Shoshan Yigal
Published: August 2024

Purpose

Cranial Nerve Neuropathies (CNNs) often accompany Cavernous Sinus Meningioma (CSM), for which Stereotactic Radiosurgery (SRS) or fractionated stereotactic radiotherapy (FSR) are established treatments. This study assesses CNNs recovery in CSM patients treated with LINAC, offering insight into treatment effectiveness.

Methods

This study was conducted on 128 patients with CSM treated with LINAC-based SRS/FSR between 2005 and 2020 at a single institution. 46 patients presented with CNNs. The study analyzed patients’ demographics, clinical parameters, SRS/FSR treatment characteristics, post-treatment CNNs recovery duration, status, and radiological control on their last follow-up.

Results

The median follow-up duration was 53.4 months. Patients were treated with SRS (n = 25) or FSR (n = 21). The mean pretreatment tumor volume was 9.5 cc decreasing to a mean end-of-follow-up tumor volume was 5.1 cc. Radiological tumor control was achieved in all cases. CNN recovery was observed in 80.4% of patients, with specific nerve recoveries documented as follows: extra-ocular nerves (43.2%), trigeminal nerve (32.4%), and optic nerve (10.8%). A higher CNNs recovery rate was associated with a smaller pre-treatment tumor volume (p < 0.001), and the median time-to-improvement was 3.7 months. Patients with tumor volumes exceeding 6.8 cc and those treated with FSR exhibited prolonged time-to-improvement (P < 0.03 and P < 0.04 respectively).

Conclusions

This study suggests that SRS/FSR for CSM provides good and sustainable CNNs recovery outcomes with excellent long-term radiological control. A higher CNNs recovery rate was associated with a smaller pre-treatment tumor volume. while shorter time-to-improvement was identified in patients treated with SRS compared to FSR, particularly in those with small pre-treatment tumor volume.
The modified 5-item frailty index as a predictor of perioperative risk in patients undergoing percutaneous nephrolithotomy
Authors: Chaker Kays , Ouanes Yassine , Marrak Mahdi , Gharbia Nader , Rahoui Moez , Mosbahi Boutheina , Bibi Mokhtar , Chedly Wassim Ben , Nouira Yassine
Published: August 2024

Introduction

The modified 5-item frailty index is a relatively new tool to assess the post-operative complication risks. In urology, there is limited literature on the impact of frailty on percutaneous nephrolithotomy (PCNL) outcomes. We aimed to compare the predictive value of the modified 5-item frailty index (mFI-5) to identify high risk patients prior to PCNL.

Methods

A database of patients undergoing PCNL, between 2015 and 2022, was analyzed. Patient frailty was assessed using the mFI-5 index. The mFI-5 index was calculated based on the presence of the five co-morbidities: congestive heart failure within 30 days prior to surgery, diabetes mellitus, chronic obstructive pulmonary disease, partially dependent or totally dependent functional health status at time of surgery, and hypertension requiring medication. Patients were grouped as not frail (mFI-5 = 0), intermediate (mFI-5 = 1), and severely frail (mFI-5 ≥ 2). Primary outcomes were 30-day postoperative complications. Secondary outcomes were hospitalization: total hospital length of stay, reoperation, and unplanned readmission.

Results

From a total of 320 PCNL patients included for analysis, 54.06% (n = 173) were not frail, 17.81% (n = 57) were intermediate, and 28.12% (n = 90) were severely frail. Frail patients were likely to be older (p = 0.002) and have a higher American Society of Anesthesiologists score (p = 0.001), chronic kidney disease (p < 0.001). Patients of intermediate or severe frailty were more likely to exhibit postoperative sepsis (p = 0.042), significant blood loss (p = 0.036) and require intensive care units admissions (p = 0.0015). Frail patients had a longer hospital length of stay (p < 0.001) and tended to require reoperation (p = 0.001), and unplanned readmission (p = 0.02).

Conclusion

Frailty assessment appears useful in stratifying those at risk of extended hospitalization, septic and hemorrhagic complications, readmission, or reoperation after PCNL. Preoperative assessment of frailty phenotype may give insight into treatment decisions and assist surgeons in counselling patients on expected course and hospital stay following PCNL.
Adherence to the Mediterranean diet and its protective effects against colorectal cancer: a meta-analysis of 26 studies with 2,217,404 participants
Authors: Ungvari Zoltan , Fekete Mónika , Fekete János Tibor , Grosso Giuseppe , Ungvari Anna , Győrffy Balázs
Published: August 2024

Colorectal cancer (CRC) is a major global health concern and represents a significant public health challenge in Hungary, where it exhibits some of the highest morbidity and mortality rates in the European Union. The Mediterranean diet has been suggested to reduce the incidence of CRC, but comprehensive evidence from diverse study designs is needed to substantiate this effect. A systematic literature search was conducted in PubMed, ClinicalTrials.gov, CENTRAL, and the Web of Science to identify randomized controlled trials and human clinical trials from 2008 to 2024 to identify relevant studies. Statistical analysis was performed using the https://metaanalysisonline.com web application using a random effects model to estimate the pooled hazard rates (HRs). Forest plots, funnel plots, and Z-score plots were utilized to visualize results. We identified 15 clinical trials and 9 case–control studies, encompassing a total of 2,217,404 subjects. The pooled analysis indicated that adherence to the Mediterranean diet significantly reduced the prevalence of CRC (HR = 0.84, 95% CI = 0.78–0.91, p < 0.01). This protective effect was consistent across sexes, with HRs of 0.85 (95% CI = 0.75–0.97, p = 0.01) for males and 0.88 (95% CI = 0.79–0.99, p = 0.03) for females. Case–control studies specifically showed a substantial effect (HR = 0.51, 95% CI = 0.38–0.68, p < 0.01). Notable heterogeneity was observed across studies, yet the a priori information size was substantially below the cumulative sample size, ensuring sufficient data for reliable conclusions. The findings from this meta-analysis reinforce the protective role of the Mediterranean diet against CRC. The results of this meta-analysis will inform dietary interventions designed to mitigate CRC risk, which are conducted within the framework of the Semmelweis Study, an ongoing comprehensive cohort study at Semmelweis University, designed to explore the multifaceted causes of unhealthy aging in Hungary. These interventions aim to explore the practical application of Mediterranean dietary patterns in reducing CRC incidence among the Hungarian population.
Fundamental characterization of lubrication effects through various cooling lubricants in the chip formation zone
Authors: Biermann D. , Saelzer J. , Bergmann B. , Schenzel J. , Menze C. J. , Gerken J. F. , Wolf T. , Denkena B. , Möhring H.-C. , Zabel A.
Published: August 2024

Using cooling lubricants in metalworking requires a high consumption of energy and resources. However, cooling lubricants serve to increase the productivity and quality of these processes. Accordingly, it is necessary to expand the efficiency of their application. This requires fundamental understanding of the working mechanisms. Driven by this motivation, this publication compares six cooling lubricants regarding their lubrication effect in orthogonal cutting. Three types of fluid supply, each conducted on a specific special machine tool for chip formation analysis, and two cutting speeds have been used in the tests. In order to analyze the lubricating effect of these different scenarios, force measurements were carried out and the chip formation was recorded with high-speed recordings. It was found that the process improvements due to lubrication is determined by the interaction of fluid properties, supply strategy and cutting speed. Moreover, clear limitations of water-based cooling lubricants (especially oil-water-emulsions) in the ability to lubricate the chip formation zone have been determined and quantified.
A survey of women diagnosed with breast cancer experiencing oncology treatment–induced hot flushes: identification of specific characteristics as predictors of hot flush occurrence, frequency, and severity
Authors: Gallagher Susan , Johnstone Alice , De Livera Alysha , Marsh Deborah J. , Walsh Sean
Published: August 2024

Purpose

More women diagnosed with breast cancer (BC) are living with oncology treatment–induced hot flushes (HFs). This Australian-based survey explores why some women experience more severe or ongoing HF and whether specific population characteristics are predictive of HF occurrence, frequency, and/or severity.

Methods

A non-probabilistic anonymous survey distributed online (Register4) and two Australian hospitals collected demographic and clinical information. Eligibility was consenting Australian-based women, 18 years and over, with a primary BC diagnosis. Analysis included linear and logistic regression models.

Results

A total of 324 survey responses were analyzed. Chemotherapy and hormone therapy were each associated with HF occurrence (aOR = 2.92, 95% CI [1.27, 6.70], p = 0.01; and aOR = 7.50, 95% CI [3.02, 18.62], p < 0.001) and in combination (aOR = 5.98, 95% CI [2.61, 13.69], p < 0.001). Increased self-reported anxiety at BC diagnosis was significantly associated with HF frequency and severity scores (aCO = 0.71, 95% CI [0.31, 1.12], p = 0.001; and aCO = 0.44, 95% CI [0.33, 0.55], p < 0.001). Postmenopausal women had significantly lower HF severity and frequency scores than premenopausal women (aCO = −0.93, 95% CI [−1.62, −0.25], p = 0.008; and aCO = −2.62, 95% CI [−5.14, −0.11], p = 0.041).

Conclusions

Women with BC receiving chemotherapy and/or hormone therapy and premenopausal or experiencing elevated anxiety and/or stress will likely experience more severe oncology treatment–related HFs.

Implications for Cancer Survivors

HFs continue across the BC treatment trajectory with women >5-year survivorship still reporting life impacts, with premenopausal women at the time of BC diagnosis at higher risk of experiencing severe and more frequent oncology treatment-induced HFs than postmenopausal women. Women at high risk require information on methods to moderate HF potential life impacts and maintain treatment compliance.
Antibiosis in small grain cereals against the rose-grain aphid, Metopolophium dirhodum (Hemiptera: Aphididae)
Authors: Saska Pavel , Skuhrovec Jiří
Published: August 2024

Resistance against aphids is an integrated pest management tactic that enhances the economic and environmental sustainability of cereal production. The aim of our study was to assess the degree of antibiosis against Metopolophium dirhodum (Walker) (Hemiptera: Aphididae), one of the most important cereal aphids in temperate regions, in two lines of small grain cereals bred in the Crop Research Institute (CRI) of Prague: spring wheat, Triticum aestivum L. cv. ‘Rufia’, and germplasm of durum wheat, Triticum turgidum ssp. durum (Desf.) van Slageren ‘TTD40363’, under controlled laboratory conditions. Resistant spring wheat cultivar (‘Libertina’) and highly susceptible spring barley (Hordeum vulgare L. cv. ‘Sebastian’) were used for reference. The responses of M. dirhodum to each line and population growth projections were determined according to the age-stage, two-sex life table theory. We found that Rufia was susceptible and TTD40363 was rather resistant to M. dirhodum. The projected population sizes after 35 days were ~ 41,000 individuals in spring wheat Rufia and ~ 12,000 in durum wheat TTD40363, which is within the range delimited by the reference cultivars (4,000 in the highly resistant spring wheat Libertina and 77,500 in highly susceptible spring barley Sebastian). This study provides new data on small grain cereal resistance to aphids. An age-stage, two-sex life table approach was used to assess resistance to aphids on durum wheat and barley for the first time.
Sunlight-driven photocatalytic degradation of methylene blue using ZnO/biochar nanocomposite derived from banana peels
Authors: Eswaran Prabakaran , Madasamy Priya Dharshini , Pillay Kriveshini , Brink Hendrik
Published: August 2024

This study describes the preparation of zinc oxide nanocomposite and its application as photocatalyst in the degradation of methylene blue under sunlight irradiation. Zinc oxide-coated biochar (ZnO/BC) nanocomposite was prepared using the hydrothermal method from banana peels and zinc acetate dihydrate as precursors. The biochar (BC), ZnO nanoparticles (ZnONPs), and ZnO/BC nanocomposite were characterized, and the results showed that ZnONPs had definite crystallinity and a regular surface morphology, with particles approximately 18 nm in size, and a XRD pattern corresponding to ZnONPs. In contrast, the ZnO/BC nanocomposite exhibited a more amorphous structure consistent with wurtzite (ZnO) and an irregular surface morphology with clusters of white particles measuring around 20–30 nm. Tauc’s plot was used to calculate the band gaps energy of ZnONPs (3.04 eV) and ZnO/BC nanocomposite (2.89 eV). Catalyst-free, ZnONPs, and ZnO/BC nanocomposite were utilized for the photocatalytic degradation of methylene blue (MB) under sunlight irradiation for 0 to 120 min in which ZnO/BC nanocomposite showed excellent photocatalytic degradation of MB under sunlight irradiation at 0 to 120 min due to lower band gap energy and synergetic effect between ZnO and BC. Dosages of 100 mg (ZnO/BC nanocomposite) and 10 ppm (MB) were optimized to obtain the best photocatalytic degradation efficiency (92 %) under sunlight irradiation with 0 to 120 min. The process was conducted with various parameters like dosage variation, concentration of MB, and different pH 3, 5, 8, and 10 to improve the photocatalytic degradation of MB from wastewater. The results indicated that the optimal conditions for the photocatalytic degradation of MB (92% after 120 min) were a catalyst dosage of 100 mg, an MB concentration of 10 ppm, and a pH of 10. This work demonstrates the potential of ZnO/BC nanocomposite photocatalyst for application in wastewater treatment and environment remediation.
Investigation of nutrition status and analysis of 180-day readmission factors in elderly hospitalized patients with COPD
Authors: Liu Huan , Song Jingsi , Wang Zhiqiang , Wu Songze , Qiu Shi , Chen Benhui , Rao Zhiyong , Jing Xiaofan
Published: August 2024

Background and objective

Malnutrition is prevalent among elderly patients with COPD, who also experience a high rate of readmission. Therefore, it is imperative to investigate the nutrition status of these patients, identify risk factors for readmission, and offer insights for clinical management. To achieve this, a cross-sectional study was conducted to investigate factors influencing nutrition status using GLIM criteria and explore the 180-day readmission factors among hospitalized elderly COPD patients.

Methords and results

The data were collected from a hospital in Southwest China, encompassing a cohort of 319 eligible patients. Among elderly hospitalized COPD patients, the prevalence of malnutrition was 49.53% (158/319). Multivariate logistic regression revealed malnutrition (OR = 3.184), very severe airway obstruction (OR = 3.735), and Number of comorbidities ≥ 3 (OR = 5.754) as significant risk factors for 180-day readmission.

Conclusions

These findings suggest that malnutrition is a prevalent issue among elderly hospitalized patients with COPD and constitutes one of the risk factors contributing to the 180-day readmission rate. Therefore, timely identification and treatment for malnourished patients are crucial.
Monte Carlo Simulation, Artificial Intelligence and Machine Learning-based Modelling and Optimization of Three-dimensional Electrochemical Treatment of Xenobiotic Dye Wastewater
Authors: Ganthavee Voravich , Fernando Merenghege M. R. , Trzcinski Antoine P.
Published: August 2024

The present study investigates the synergistic performance of the three-dimensional electrochemical process to decolourise methyl orange (MO) dye pollutant from xenobiotic textile wastewater. The textile dye was treated using electrochemical technique with strong oxidizing potential, and additional adsorption technology was employed to effectively remove dye pollutants from wastewater. Approximately 98% of MO removal efficiency was achieved using 15 mA/cm2 of current density, 3.62 kWh/kg of energy consumption and 79.53% of current efficiency. The 50 mg/L MO pollutant was rapidly mineralized with a half-life of 4.66 min at a current density of 15 mA/cm2. Additionally, graphite intercalation compound (GIC) was electrically polarized in the three-dimensional electrochemical reactor to enhance the direct electrooxidation and.OH generation, thereby improving synergistic treatment efficiency. Decolourisation of MO-polluted wastewater was optimized by artificial intelligence (AI) and machine learning (ML) techniques such as Artificial Neural Networks (ANN), Support Vector Machine (SVM), and random forest (RF) algorithms. Statistical metrics indicated the superiority of the model followed this order: ANN > RF > SVM > Multiple regression. The optimization results of the process parameters by artificial neural network (ANN) and random forest (RF) approaches showed that a current density of 15 mA/cm2, electrolysis time of 30 min and initial MO concentration of 50 mg/L were the best operating parameters to maintain current and energy efficiencies of the electrochemical reactor. Finally, Monte Carlo simulations and sensitivity analysis showed that ANN yielded the best prediction efficiency with the lowest uncertainty and variability level, whereas the predictive outcome of random forest was slightly better.

Highlights

• In-depth analysis of various artificial intelligence optimization techniques.

• Prediction efficiency of artificial intelligence and machine learning algorithms.

• 98% dye removal and 100% regeneration of graphite intercalation compound.

• Advanced statistical analysis of targeted responses and data fitting techniques.

• Analysis of uncertainties and variability using Monte Carlo simulation.
Injectable Nanorobot-Hydrogel Superstructure for Hemostasis and Anticancer Therapy of Spinal Metastasis
Authors: Chen Qing , Yan Miao , Hu Annan , Liang Bing , Lu Hongwei , Zhou Lei , Ma Yiqun , Jia Chao , Su Dihan , Kong Biao , Hong Wei , Jiang Libo , Dong Jian
Published: August 2024

Surgery remains the standard treatment for spinal metastasis. However, uncontrolled intraoperative bleeding poses a significant challenge for adequate surgical resection and compromises surgical outcomes. In this study, we develop a thrombin (Thr)-loaded nanorobot-hydrogel hybrid superstructure by incorporating nanorobots into regenerated silk fibroin nanofibril hydrogels. This superstructure with superior thixotropic properties is injected percutaneously and dispersed into the spinal metastasis of hepatocellular carcinoma (HCC) with easy bleeding characteristics, before spinal surgery in a mouse model. Under near-infrared irradiation, the self-motile nanorobots penetrate into the deep spinal tumor, releasing Thr in a controlled manner. Thr-induced thrombosis effectively blocks the tumor vasculature and reduces bleeding, inhibiting tumor growth and postoperative recurrence with Au nanorod-mediated photothermal therapy. Our minimally invasive treatment platform provides a novel preoperative therapeutic strategy for HCC spinal metastasis effectively controlling intraoperative bleeding and tumor growth, with potentially reduced surgical complications and enhanced operative outcomes.
Identifying payable cluster distributions for improved reservoir characterization: a robust unsupervised ML strategy for rock typing of depositional facies in heterogeneous rocks
Authors: Ashraf Umar , Anees Aqsa , Zhang Hucai , Ali Muhammad , Thanh Hung Vo , Yuan Yujie
Published: August 2024

The oil and gas industry relies on accurately predicting profitable clusters in subsurface formations for geophysical reservoir analysis. It is challenging to predict payable clusters in complicated geological settings like the Lower Indus Basin, Pakistan. In complex, high-dimensional heterogeneous geological settings, traditional statistical methods seldom provide correct results. Therefore, this paper introduces a robust unsupervised AI strategy designed to identify and classify profitable zones using self-organizing maps (SOM) and K-means clustering techniques. Results of SOM and K-means clustering provided the reservoir potentials of six depositional facies types (MBSD, DCSD, MBSMD, SSiCL, SMDFM, MBSh) based on cluster distributions. The depositional facies MBSD and DCSD exhibited high similarity and achieved a maximum effective porosity (PHIE) value of ≥ 15%, indicating good reservoir rock typing (RRT) features. The density-based spatial clustering of applications with noise (DBSCAN) showed minimum outliers through meta cluster attributes and confirmed the reliability of the generated cluster results. Shapley Additive Explanations (SHAP) model identified PHIE as the most significant parameter and was beneficial in identifying payable and non-payable clustering zones. Additionally, this strategy highlights the importance of unsupervised AI in managing profitable cluster distribution across various geological formations, going beyond simple reservoir characterization.
A Corpus Pragmatics Approach to Active Listenership in Conversations in British English: Contextualised Function-To-Form
Authors: Gerigk Kevin Frank
Published: August 2024

Active Listenership are the features that refer to the linguistic behaviour of the listener in casual conversations. The listener continuously utters Listener Response Tokens, Sentence-Completions and Which-Comment-Clauses to signal emotional and social involvement in the discourse. Particularly in the field of corpus pragmatics, Active Listenership has found attention over the past two decades. In this paper, I introduce a novel context-driven function-to-form corpus pragmatics annotation scheme. The scheme is applied to a down-sampled version of the spoken BNC2014, and subsequently evaluated in terms of inter-rater plausibility. Then, I present the qualitative findings on how frequent the features of Active Listenership are in the corpus in general. Subsequently, I analyse the contextual units (as per my annotation scheme) to show which feature of Active Listenership is most likely to occur in a specific speech context. I finish this paper with suggestions for future research and a call to include more features of conversational English into an elaboration of the annotation scheme. My findings can be applied to general pragmatics research and English Language Teaching.
Facile synthesis of Mn-doped CdS nanoparticles on carbon quantum dots: towards efficient photocatalysis
Authors: Orak Ceren , Oğuz Taha , Horoz Sabit
Published: August 2024

This study explores the synthesis and application of carbon quantum dots (CQDs)-based composite photocatalysts, including CQDs, CdS@CQDs, and Mn-doped CdS@CQDs, for the degradation of methylene blue (MB) and Reactive Black 5 (RB5) through photocatalysis. The synthesis of the photocatalysts involved a meticulous procedure utilizing olive oil as a precursor. Characterization studies employing transmission electron microscopy (TEM), X-ray diffractometer (XRD), and Brunauer-Emmett-Teller (BET) surface area confirmed the successful synthesis of the composite photocatalysts with well-dispersed nanoparticles and varying surface areas. Photocatalytic degradation experiments revealed that Mn-doped CdS@CQDs exhibited the highest degradation efficiency for both MB and RB5 under optimized reaction conditions, with pH identified as the most significant parameter, and statistical analyses supported the validity of the experimental data. Based on the results, the highest MB degradation efficiency (99.87%) was achieved at the following reaction conditions: pH = 9, catalyst amount = 0.55 g/L and initial hydrogen peroxide concentration (HPC) = 1 mM while the highest RB5 degradation efficiency (98.15%) was obtained at the following reaction conditions: pH = 3, catalyst amount = 1 g/L and HPC = 0.55 mM. Comparison with the literature showcased the competitive performance of the synthesized photocatalysts, achieving higher efficiencies with lower amounts of photocatalysts and hydrogen peroxide. Kinetic studies revealed that the first-order reaction kinetic was observed in both MB and RB5 degradation. This comprehensive investigation underscores the potential of Mn-doped CdS@CQDs as efficient photocatalysts for wastewater treatment, offering insights for future research and application in environmental remediation efforts.
Colorectal cancer image recognition algorithm based on improved transformer
Authors: Qin Zhuanping , Sun Wenhao , Guo Tinghang , Lu Guangda
Published: August 2024

Aiming at the problems of the complex background of colorectal cancer tissue cell images and the difficulty of detection caused by the low differentiation of cancer cell regions, a deep learning method is used to detect the cancer cell regions. By integrating the skip feedback connection structure into U-Net and combining it with the Swin Transformer for feature extraction, we improve the multi-level feature extraction capabilities of the model. This algorithm enables end-to-end recognition of colorectal adenocarcinoma tissue images and achieves an accuracy of 95.8% on the NCT-CRC-HE-100K dataset, demonstrating its potential to significantly support colorectal cancer detection and treatment.
Scaling up in community forest enterprises: the case of central Mexico
Authors: Solís-Mendoza Lesly Elizabeth , Sánchez-Nupan Laura Oliva , Castro-Torres Ricardo Balam , De la Mora de la Mora Gabriela , Kozak Rob , Peterson St Laurent Guillaume , Guerra de la Cruz Vidal , Galicia Leopoldo
Published: August 2024

For community forest enterprises (CFEs) in central Mexico, ‘scaling up’ can be an effective means of achieving the transition to economically attractive and sustainable forest management, but little is known about the potential and challenges that they face in this regard. We used a qualitative case study to evaluate a set of variables that determine the limitations and opportunities for scaling up CFEs in central Mexico and thereby expanding their commercial capacities, activities and outputs. The framework included concepts related to sustainable forest management, natural resource governance and temperate forest ecology. We interviewed leaders of four communities (n = 30) and 15 external actors (regional industry, and national non-governmental organizations). Communities that had developed long-term plans for forest management that embrace conservation values were also those with the greatest capacity to generate sustainable income streams from diverse sources. The robust legal frameworks and community institutions that set up procedures for responsibly harvesting and selling timber, thereby generating income, offer opportunities to enhance the effectiveness of CFEs. Demand continues to grow for wood products involving skilled crafts in central Mexico, but local production remains low; a lack of access to finance imposes limits on investment in the forests and value-added options for the products and services. Market opportunities and growth are also restricted by substandard physical infrastructure (e.g., roads, electricity) limited access to finance (e.g., credit, private-sector investors), and an absence of business plans. There are no formal networks to facilitate learning among these CFEs. Scaling up for these CFEs will require access to markets, innovations, and finance to create sustainable value chains for wood and non-wood forest products. The Mexican government could be instrumental in this by incorporating the notion of scaling up for CFEs when enacting policy that builds on and supports the country’s proven models of community-based forest management. On the other hand, this approach can be useful for developing more robust theoretical and methodological frameworks that capture these complex dynamics, contribute to the theory and practice of enterprise forestry development, sustainable natural resource management, and effective policy formulation.
The coevolution of technology, markets, and culture: the challenging case of AI
Authors: Muñoz Félix-Fernando
Published: August 2024

Artificial intelligence (AI) is at the center of economic, social, political, and ethical debate. For the first time in human history, since the appearance of writing, a new type of “intelligence” is impacting the very nature of social relationships. New technologies are not only changing the operating model of markets and value chains in an accelerated way but also in how information is generated and processed, how labor, social relations, and culture evolve, etc. In this paper, we pursue two main goals. First, to set up an analytical framework in which cognitive, technical, and cultural dynamics are intertwined with the processes of deployment of economic action. Secondly, we utilize this framework to explore some key features and challenges of AI and its impact on coevolutionary processes at the cognitive, market, and cultural levels. We devote special attention to the consequences that AI may have for the concept of (economic) rationality and the formation of action plans. We conclude that AI will massively enhance agents’ spaces of action by improving efficiency and exploring new possibilities. However, AI will not change the nature of human action and the structure of the evolution of the economic system.