bluuebunny/crossref_metadata_2025 huggingface dataset:
The Discourse on Perspective in Giovanni Paolo Lomazzo’s Trattato dell’Arte della Pittura
Authors: Tramelli Barbara
Published: April 2023

The paper presents the complex discourse on perspective which the Milanese painter Giovanni Paolo Lomazzo writes in book V of his Trattato dell’Arte della Pittura (1584), explaining why the theoretical and practical discourse on the subject can be interpreted as the result of the artist’s erudition, personal connections and direct artistic experience.
Invariant affine subspaces
Authors: Wójcik Paweł
Published: April 2023

We study the problem: whether a given operator on a Banach space has an invariant affine subspace. We examine the existence or non-existence of such affine subspaces. Moreover, we give some applications.
NOX4-derived ROS are neuroprotective by balancing intracellular calcium stores
Authors: Gola Lukas , Bierhansl Laura , Csatári Júlia , Schroeter Christina B. , Korn Lisanne , Narayanan Venu , Cerina Manuela , Abdolahi Sara , Speicher Anna , Hermann Alexander M. , König Simone , Dinkova-Kostova Albena T. , Shekh-Ahmad Tawfeeq , Meuth Sven G. , Wiendl Heinz , Gorji Ali , Pawlowski Matthias , Kovac Stjepana
Published: April 2023

Hyperexcitability is associated with neuronal dysfunction, cellular death, and consequently neurodegeneration. Redox disbalance can contribute to hyperexcitation and increased reactive oxygen species (ROS) levels are observed in various neurological diseases. NOX4 is an NADPH oxidase known to produce ROS and might have a regulating function during oxidative stress. We, therefore, aimed to determine the role of NOX4 on neuronal firing, hyperexcitability, and hyperexcitability-induced changes in neural network function. Using a multidimensional approach of an in vivo model of hyperexcitability, proteomic analysis, and cellular function analysis of ROS, mitochondrial integrity, and calcium levels, we demonstrate that NOX4 is neuroprotective by regulating ROS and calcium homeostasis and thereby preventing hyperexcitability and consequently neuronal death. These results implicate NOX4 as a potential redox regulator that is beneficial in hyperexcitability and thereby might have an important role in neurodegeneration.
Relationships between stiffness of material, lamellas and CLT elements with respect to out of plane bending and rolling shear
Authors: Olsson Anders , Schirén Whokko , Segerholm Kristoffer , Bader Thomas K.
Published: April 2023

The use of cross laminated timber (CLT) for construction has increased greatly in recent years and the large volumes of wood used for CLT means that it is important to optimize the use of the material. This requires relevant grading of lamellas and knowledge of relationships between lamella and CLT properties. In the present study, the relationship between dynamic axial modulus of elasticity (MoE) of lamellas and the quasi-static out of plane bending stiffness of CLT is investigated. By means of four-point bending test, it is shown that the effective quasi-static MoE of lamellas in CLT is only 2–6% lower than the average axial dynamic MoE of the individual lamellas. With this knowledge, producers of CLT can easily predict and control the important out of plane bending stiffness of the produced CLT. Moreover, it is shown that effective rolling shear stiffness of layers in CLT can be accurately determined by means of digital image correlation performed in connection to four-point bending of CLT, even for long test spans. For layers of lamellas of Scots pine of size 40 × 190 mm2the average apparent or effective rolling shear modulus was determined to be 159 MPa. The average rolling shear modulus of the same material was determined to be 56 MPa.
Funktionelle Diagnostik der patellofemoralen Instabilität
Authors: Bartsch Anna , Egloff Christian
Published: April 2023

Hintergrund

Die Routinediagnostik der patellofemoralen Instabilität evaluiert überwiegend statische Faktoren. Obwohl es sich bei der Instabilität um ein dynamisches Geschehen handelt, wird statisches Malalignement und nicht Maltracking als Surrogat für die patellofemorale Instabilität erfasst. Mehrere statische Parameter wie TT-TG-Abstand (Distanz zwischen Tuberositas tibiae und Trochlearinne) oder Patellahöhe ändern sich mit der Beinposition, und durch die Kontraktion des M. quadriceps femoris kann sich die Position der Patella um über ein Viertel ihrer Breite mediolateral verschieben. Funktionelle Diagnostik, die das Patellatracking erfasst, beschreibt eine patellofemorale Instabilität daher differenzierter als eine alleinige statische Diagnostik.

Ergebnisse

Um als funktionelle Diagnostik eingesetzt zu werden, muss die Patellabewegung in verschiedenen Kniewinkeln, mit unterschiedlich hoher Anspannung des Quadrizeps, unter externer Stressbelastung und unter Belastung im Stehen durchgeführt werden können. Als neue Methoden zur funktionellen Diagnostik haben sich Ultraschall, dynamische Magnetresonanztomographie (MRT) und muskuloskeletale Modellierung in unterschiedlichen Anwendungsbereichen hervorgetan, die ein großes Potenzial zeigen, diese diagnostische Lücke zu schließen. Die Sonographie kann in der Sprechstunde einfach durchgeführt und wiederholt werden, die dynamische MRT kann eine hochauflösende Aussage über Translation und Rotation inkl. Knorpelevaluation bieten, und die muskuloskeletale Modellierung kann Gelenkbelastungskräfte während der physiologischen Ambulation bestimmen.

Diskussion

Funktionelle Diagnostik der patellofemoralen Instabilität eröffnet neue Perspektiven und erlaubt eine tiefgreifende Analyse der patellofemoralen Biomechanik. Referenzwerte und spezifische Bewegungen für den Einsatz in Diagnose, Behandlung und Nachsorge müssen jedoch noch spezifiziert werden.
Biofertilizer effect of some zinc dissolving bacteria free and encapsulated on Zea mays growth
Authors: Sultan Asmaa Ahmed Yassen Ahmed , Gebreel Hassan Mahmoud , Youssef HebatAllah Ibrahim AbdElazeim
Published: April 2023

Crop nutrition depends on zinc for enzymatic, oxidative, and metabolic processes. In the current study 20 different bacteria were isolated from five soil samples collected from different fields in Egypt. Bacterial isolates were screened for their ability to solubilize insoluble zinc oxide and zinc carbonate. The ability of selected isolates to tolerate soluble zinc was determined using different concentrations of (ZnSO4). Three bacterial isolates were selected with efficiency in solubilizing zinc oxide and zinc carbonate while tolerating high levels of soluble zinc. Molecular identification by 16S rRNA sequencing of the chosen isolates identified them as B3 (Acinetobacter calcoaceticus), B5 (Bacillus proteolyticus) and C6 (Stenotrophomonas pavanii). Sodium alginate beads formulated with the isolated bacteria were tested for stability under different storage conditions for 3 months. A pot experiment was conducted to study and compare the effect of using chosen isolates as an in vivo Zn solubilizer with amended ZnCO3 either alone or embedded in beads as carrier in the soil and its effect on growth parameters of Zea mays after 2 months. There was an increase in Zn uptake in all treatments compared to the control. However, plants grown in a pot treated with ZnCO3 and Acinetobacter calcoaceticus showed the highest zinc content and plant dry weight as compared to the control. Finally, selected isolates in both free and encapsulated forms showed improved plant growth parameters and higher zinc content and can be applied as biofertilizers to enhance soil fertility.
The role of warm ischemia time on functional outcomes after robotic partial nephrectomy: a radionuclide renal scan study from the clock randomized trial
Authors: Antonelli Alessan dro , Cindolo Luca , Sandri Marco , Veccia Alessandro , Annino Filippo , Bertagna Francesco , Di Maida Fabrizio , Celia Antonio , D’Orta Carlo , De Concilio Bernardino , Furlan Maria , Giommoni Valentina , Ingrosso Manuela , Mari Andrea , Nucciotti Roberto , Olianti Catia , Porreca Angelo , Primiceri Giulia , Schips Luigi , Sessa Francesco , Bove Pierluigi , Simeone Claudio , Minervini Andrea ,   The AGILE Group (Italian Group for Advanced Laparo-Endoscopic Surgery)
Published: April 2023

Purpose

To evaluate the relationship between warm ischemia time (WIT) duration and renal function after robot-assisted partial nephrectomy (RAPN).

Methods

The CLOCK trial is a phase 3 randomized controlled trial comparing on- vs off-clamp RAPN. All patients underwent pre- and postoperative renal scintigraphy. Six-month absolute variation of eGFR (AV-GFR), rate of relative variation in eGFR over 25% (RV-GFR > 25), absolute variation of split renal function (SRF) at scintigraphy (AV-SRF).

The relationships WIT/outcomes were assessed by correlation graphs and then modeled by uni- and multivariable regression.

Results

324 patients were included (206 on-clamp, 118 off-clamp RAPN). Correlation graphs showed a threshold on WIT equal to 10 min. The differences in outcome measures between cases with WIT < vs ≥ 10 min were: AV-GFR − 3.7 vs − 7.5 ml/min (p < 0.001); AV-SRF − 1% vs − 3.6% (p < 0.001); RV-GFR > 25 9.3% vs 17.8% (p = 0.008). Multivariable models found that AV-GFR was related to WIT ≥ 10 min (regression coefficient [RC] − 0.52, p = 0.019), age (RC − 0.35, p = 0.001) and baseline eGFR (RC − 0.30, p < 0.001); RV-GFR > 25 to WIT ≥ 10 min (odds ratio [OR] 1.11, p = 0.007) and acute kidney injury defined as > 50% increase in serum creatinine (OR 19.7, p = 0.009); AV-SRF to WIT ≥ 10 min (RC − 0.30, p = 0.018), baseline SRF (RC − 0.76, p < 0.001) and RENAL score (RC − 0.60. p = 0.028).

The main limitation was that the CLOCK trial was designed on a different endpoint and therefore the present analysis could be underpowered.

Conclusions

Up to 10 min WIT had no consequences on functional outcomes. Above the 10-min threshold, a statistically significant, but clinically negligible impact was found.
Short-term outcome of diverting loop ileostomy reversals performed by residents: a retrospective cohort prognostic factor study
Authors: von Savigny Clara , Juratli Mazen A. , Koch Christine , Gruber-Rouh Tatjana , Bechstein Wolf O. , Schreckenbach Teresa
Published: April 2023

Aim

The reversal of diverting loop ileostomy (DLI) is one of surgical trainees’ first procedures. Complications of DLI reversal can cause life-threatening complications and increase patient morbidity. This study compared DLI reversals performed by surgical trainees with those by attending surgeons.

Method

This retrospective cohort study was performed at a single primary care center on 300 patients undergoing DLI reversal. The primary outcome was morbidity, according to the Clavien-Dindo classification (CDC), with special attention paid to the surgeon’s level of training. The secondary endpoint was postoperative intestinal motility dysfunction.

Results

Surgical trainees had significantly longer operation times (p < 0.001) than attending surgeons. Univariate analyses revealed no influence on the level of training for postoperative morbidity. First bowel movement later than 3 days after surgery was a significant risk factor for CDC $$\ge$$
≥
3 (OR, 4.348; 96% CI, 1670–11.321; p = 0.003). Independent risk factors for surgical site infections (SSIs) were an elevated BMI (OR, 1.162; 95% CI, 1.043–1.1294; p = 0.007) and a delayed bowel movement (OR, 3.973; 95% CI, 1.300–12.138; p = 0.015). For postoperative intestinal motility dysfunction, an independent risk factor was a primary malignant disease (OR, 1.980; 95% CI, 1.120–3.500; p = 0.019), and side-to-side stapled anastomosis was a protective factor (OR, 0.337; 95% CI 0.155–0.733; p = 0.006).

Conclusion

Even though surgical trainees needed significantly more time to perform the surgery, the level of surgical training was not a risk factor for increased postoperative morbidity. Instead, delayed first bowel movement was predictive of SSI.
Serum neurofilament light chain levels are associated with all-cause mortality in the general US population
Authors: Ciardullo Stefano , Muraca Emanuele , Bianconi Eleonora , Ronchetti Celeste , Cannistraci Rosa , Rossi Laura , Perra Silvia , Zerbini Francesca , Perseghin Gianluca
Published: April 2023

Introduction

Serum neurofilament light chain (sNfL) levels are biomarkers of neuro-axonal injury in multiple neurological diseases. Little is known on their potential role as prognostic markers in people without known neurological conditions.

Objective

The aim of this study is to evaluate the association between sNfL levels and all-cause mortality in a general population setting.

Methods

sNfL levels were measured in 2071 people aged 25–75 years from the general US population that participated in the 2013–2014 cycles of the National Health and Nutrition Examination Survey (NHANES). Cognitive function was evaluated in a subset of participants aged 60–75 years using the Consortium to Establish a Registry for Alzheimer’s Disease-Word Learning test, the Animal Fluency test and the Digit Symbol Substitution test. We applied Cox proportional hazard models adjusted for several potential confounders to evaluate the association between sNfL and all-cause mortality through December 2019 by linking NHANES data with data from the National Death Index.

Results

In a cross-sectional analysis, higher sNfL levels were associated with worse performance in all three cognitive function tests. Over a median follow-up of 6.1 years, 85 participants died. In a multivariable model adjusted for age, sex, race-ethnicity, diabetes, chronic kidney disease, harmful alcohol consumption, cigarette smoke and prevalent cardiovascular disease, higher sNfL levels were significantly and positively associated with all-cause mortality (HR per unit increase in log-transformed sNfL: 2.46, 95% CI 1.77–3.43, p < 0.001). Results were robust when analyses were stratified according to age, sex, body mass index and kidney function.

Conclusion

We found a positive association between sNfL levels and mortality in the general US population. Further studies are needed to understand the biological mechanisms underlying this association.
Parameterised Counting in Logspace
Authors: Haak Anselm , Meier Arne , Prakash Om , Rao B. V. Raghavendra
Published: April 2023

Logarithmic space-bounded complexity classes such as$$\textbf{L} $$Land$$\textbf{NL} $$NLplay a central role in space-bounded computation. The study of counting versions of these complexity classes have lead to several interesting insights into the structure of computational problems such as computing the determinant and counting paths in directed acyclic graphs. Though parameterised complexity theory was initiated roughly three decades ago by Downey and Fellows, a satisfactory study of parameterised logarithmic space-bounded computation was developed only in the last decade by Elberfeld, Stockhusen and Tantau (IPEC 2013, Algorithmica 2015). In this paper, we introduce a new framework for parameterised counting in logspace, inspired by the parameterised space-bounded models developed by Elberfeld, Stockhusen and Tantau. They defined the operators$$\textbf{para}_{\textbf{W}}$$paraWand$$\textbf{para}_\beta $$paraβfor parameterised space complexity classes by allowing bounded nondeterminism with multiple-read and read-once access, respectively. Using these operators, they characterised the parameterised complexity of natural problems on graphs. In the spirit of the operators$$\textbf{para}_{\textbf{W}}$$paraWand$$\textbf{para}_\beta $$paraβby Stockhusen and Tantau, we introduce variants based on tail-nondeterminism,$$\textbf{para}_{{\textbf{W}}[1]}$$paraW[1]and$$\textbf{para}_{\beta {\textbf{tail}}}$$paraβtail. Then, we consider counting versions of all four operators and apply them to the class$$\textbf{L} $$L. We obtain several natural complete problems for the resulting classes: counting of paths in digraphs, counting first-order models for formulas, and counting graph homomorphisms. Furthermore, we show that the complexity of a parameterised variant of the determinant function for (0, 1)-matrices is$$\#\textbf{para}_{\beta {\textbf{tail}}}\textbf{L} $$#paraβtailL-hard and can be written as the difference of two functions in$$\#\textbf{para}_{\beta {\textbf{tail}}}\textbf{L} $$#paraβtailL. These problems exhibit the richness of the introduced counting classes. Our results further indicate interesting structural characteristics of these classes. For example, we show that the closure of$$\#\textbf{para}_{\beta {\textbf{tail}}}\textbf{L} $$#paraβtailLunder parameterised logspace parsimonious reductions coincides with$$\#\textbf{para}_\beta \textbf{L} $$#paraβL. In other words, in the setting of read-once access to nondeterministic bits, tail-nondeterminism coincides with unbounded nondeterminism modulo parameterised reductions. Initiating the study of closure properties of these parameterised logspace counting classes, we show that all introduced classes are closed under addition and multiplication, and those without tail-nondeterminism are closed under parameterised logspace parsimonious reductions. Finally, we want to emphasise the significance of this topic by providing a promising outlook highlighting several open problems and directions for further research.
Gastrectomy reduces pancreatic secretory function via pancreatic atrophy
Authors: Satoi Shumpei , Kimura Yutaka , Shimizu Rie , Matsumoto Masataka , Kawaguchi Kohei , Yoshida Yuta , Murase Takaaki , Kamei Keiko , Matsumoto Ippei , Nakai Takuya , Takeyama Yoshifumi
Published: April 2023

Purpose

Although reports suggest that the pancreatic volume decreases after gastrectomy for gastric cancer, the relationship between the pancreatic volume and secretory function after gastrectomy remains unclear. In this study, we examined the relationship between the pancreatic volume and exocrine and endocrine functions after total gastrectomy.

Methods

The pancreatic volumes of 18 distal gastrectomy and 15 total gastrectomy patients were retrospectively measured using computed tomography volumetry up to 5 years postoperatively. Ten low anterior resection patients were selected as controls. In addition, the pancreatic volume and exocrine function evaluated by fecal elastase and the insulin secretory function evaluated by glucagon tolerance testing were prospectively examined before and one year after surgery in nine cases of total gastrectomy.

Results

After low anterior resection, the pancreatic volume did not change, but after distal and total gastrectomy, the pancreatic volume decreased continuously until the fifth year. After total gastrectomy, fecal elastase decreased significantly from 865.8 μg/g to 603.2 μg/g in the first year (p = 0.0316), and the insulin secretion capacity also decreased significantly from 3.83 ng/mL to 2.26 ng/mL (p = 0.0019).

Conclusions

The pancreatic volume decreases continuously after gastrectomy for gastric cancer, and the pancreatic exocrine and endocrine functions decrease along with pancreatic atrophy after total gastrectomy.
The impact of membrane perforation and L-PRF for vertical ridge augmentation with a xenogeneic block graft: an experimental study in a canine model
Authors: Eldabe Abdelrahman K. , Abdel-Ghaffar Khaled A. , Amr Ahmed E. , Abu-Seida Ashraf M. , Abdelhamid Ehab S. , Gamal Ahmed Y.
Published: April 2023

Objectives

This study evaluated clinically and histologically the efficacy of modified perforated collagen membrane (PCM) and/or leukocyte- and platelet-rich fibrin (L-PRF) in combination with xenogeneic block bone graft in the vertical alveolar ridge augmentation.

Materials and methods

Six adult mongrel dogs were enrolled in this randomized blinded study. After defect preparation, xenogeneic screw-fixed block graft was covered by an occlusive collagen membrane in group 1 that represented the control group (Block + CM). In group 2, L-PRF membrane was added first before top coverage by occlusive collagen membrane (Block + L-PRF + CM). Groups 3 (Block + PCM) and 4 (Block + L-PRF + PCM) were identical to the first two groups except that the occlusive collagen membrane was replaced by a perforated one. Following a healing period of 2 months, the dogs were submitted to the surgical reentry phase for clinical and histological evaluation.

Results

Clinically, no significant differences were found among all groups regarding vertical and horizontal ridge dimensions (p = 0.155, 0.492, respectively). Histomorphometric analysis revealed that the percentage of the total bone area and mature bone was significantly higher in group 4 (69.36 ± 2.72, 33.11 ± 5.18) compared to the control group (59.17 ± 4.27, 21.94 ± 2.86) (p = 0. 027, p = 0.029).

Conclusion

The use of xenogenic block grafts in combination with a double-layered perforated collagen L-PRF membrane in vertical ridge augmentation appeared to improve the inductive power of this challenging defect type.

Clinical relevance

Size and number of perforations may affect the mechanical and handling properties of the membrane.
The power of typed affine decision structures: a case study
Authors: Nolte Gerrit , Schlüter Maximilian , Murtovi Alnis , Steffen Bernhard
Published: April 2023

TADS are a novel, concise white-box representation of neural networks. In this paper, we apply TADS to the problem of neural network verification, using them to generate either proofs or concise error characterizations for desirable neural network properties. In a case study, we consider the robustness of neural networks to adversarial attacks, i.e., small changes to an input that drastically change a neural networks perception, and show that TADS can be used to provide precise diagnostics on how and where robustness errors a occur. We achieve these results by introducing Precondition Projection, a technique that yields a TADS describing network behavior precisely on a given subset of its input space, and combining it with PCA, a traditional, well-understood dimensionality reduction technique. We show that PCA is easily compatible with TADS. All analyses can be implemented in a straightforward fashion using the rich algebraic properties of TADS, demonstrating the utility of the TADS framework for neural network explainability and verification. While TADS do not yet scale as efficiently as state-of-the-art neural network verifiers, we show that, using PCA-based simplifications, they can still scale to medium-sized problems and yield concise explanations for potential errors that can be used for other purposes such as debugging a network or generating new training samples.
Enhanced aerial vehicle system techniques for detection and tracking in fog, sandstorm, and snow conditions
Authors: Talaat Amira Samy , El-Sappagh Shaker
Published: April 2023

Unmanned aerial vehicles are rapidly being utilized in surveillance and traffic monitoring because of their great mobility and capacity to cover regions at various elevations and positions. It is a challenging task to detect vehicles due to their various shapes, textures, and colors. One of the most difficult challenges is correctly detecting and counting aerial view vehicles in real time for traffic monitoring objectives using aerial images and videos. In this research, strategies are presented for improving the detection ability of self-driving vehicles in tough conditions, also for traffic monitoring, vehicle surveillance. We make classification, tracking trajectories, and movement calculation where fog, sandstorm (dust), and snow conditions are challenging. Initially, image enhancement methods are implemented to improve unclear images of roads. The improved images are then subjected to an object detection and classification algorithm to detect vehicles. Finally, new methods were evaluated (Corrected Optical flow/Corrected Kalman filter) to get the least error of trajectories. Also features like vehicle count, type, tracking trajectories by (Optical flow, Kalman Filter, Euclidean Distance) and relative movement calculation are extracted from the coordinates of the observed objects. These techniques aim to improve vehicle detection, tracking, and movement over aerial views of roads especially in bad weather. As a result, for aerial view vehicles in bad weather, our proposed method has an error of less than 5 pixels from the actual value and give the best results. This improves detection and tracking performance for aerial view vehicles in bad weather conditions.
Review of carbon emissions offsetting guidelines using instructional criteria
Authors: Helppi Olli , Salo Esko , Vatanen Saija , Pajula Tiina , Grönman Kaisa
Published: April 2023

Purpose

Carbon offsetting is one of the tools that companies can use to achieve their climate targets. The ability of a company to offset its emissions successfully depends on the availability and quality of guidance on the subject. This study explores how well existing offsetting guidelines equip corporations to achieve successful emissions offsetting.

Methods

Instructional criteria were developed and used to evaluate seven guidelines. The contents of each guideline were assessed based on how they instruct a company to achieve emissions offsetting that fulfills five criteria for appropriate offsetting: target affiliation, Paris compatibility, effectiveness, prioritizing removals, and transparency.

Results and discussion

The review revealed that necessary instructions enabling appropriate emissions offsetting were absent in the guidelines. Moreover, the degree of climate ambition and the role of offsetting varied between guidelines. Deficiencies in emissions offsetting guidance may increase the uncertainty of companies’ succeeding in offsetting their emissions.

Conclusions

Developing guidance on emissions offsetting could benefit society and corporations by increasing the certainty of achieving successful emissions offsetting. Standardizing corporate emissions offsetting could be considered as one solution for unifying the practice. The practical life-cycle implications of current ambiguity in guidelines are a direction for future research.
Deep learning-based overall survival prediction model in patients with rare cancer: a case study for primary central nervous system lymphoma
Authors: She Ziyu , Marzullo Aldo , Destito Michela , Spadea Maria Francesca , Leone Riccardo , Anzalone Nicoletta , Steffanoni Sara , Erbella Federico , Ferreri Andrés J. M. , Ferrigno Giancarlo , Calimeri Teresa , De Momi Elena
Published: April 2023

Purpose

Primary central nervous system lymphoma (PCNSL) is a rare, aggressive form of extranodal non-Hodgkin lymphoma. To predict the overall survival (OS) in advance is of utmost importance as it has the potential to aid clinical decision-making. Though radiomics-based machine learning (ML) has demonstrated the promising performance in PCNSL, it demands large amounts of manual feature extraction efforts from magnetic resonance images beforehand. deep learning (DL) overcomes this limitation.

Methods

In this paper, we tailored the 3D ResNet to predict the OS of patients with PCNSL. To overcome the limitation of data sparsity, we introduced data augmentation and transfer learning, and we evaluated the results using r stratified k-fold cross-validation. To explain the results of our model, gradient-weighted class activation mapping was applied.

Results

We obtained the best performance (the standard error) on post-contrast T1-weighted (T1Gd)—area under curve $$=0.81(0.03)$$

=
0.81
(
0.03
)

, accuracy $$=0.87(0.07)$$

=
0.87
(
0.07
)

, precision $$=0.88(0.07)$$

=
0.88
(
0.07
)

, recall $$=0.88(0.07)$$

=
0.88
(
0.07
)

and F1-score $$=0.87(0.07)$$

=
0.87
(
0.07
)

, while compared with ML-based models on clinical data and radiomics data, respectively, further confirming the stability of our model. Also, we observed that PCNSL is a whole-brain disease and in the cases where the OS is less than 1 year, it is more difficult to distinguish the tumor boundary from the normal part of the brain, which is consistent with the clinical outcome.

Conclusions

All these findings indicate that T1Gd can improve prognosis predictions of patients with PCNSL. To the best of our knowledge, this is the first time to use DL to explain model patterns in OS classification of patients with PCNSL. Future work would involve collecting more data of patients with PCNSL, or additional retrospective studies on different patient populations with rare diseases, to further promote the clinical role of our model.
A new genus, Complexispora, with two new species, C. multistratosa and C. mediterranea, and Epigeocarpum japonicum sp. nov.
Authors: Błaszkowski Janusz , Yamato Masahide , Niezgoda Piotr , Zubek Szymon , Milczarski Paweł , Malinowski Ryszard , Meller Edward , Malicka Monika , Goto Bruno Tomio , Uszok Sylwia , Casieri Leonardo , Magurno Franco
Published: April 2023

Morphological analyses of three glomoid spore-producing fungi suggested that two of them were undescribed species of Glomeraceae (phylum Glomeromycota), and the third differed slightly from Dominikia glomerocarpica and Epigeocarpum crypticum, recently described in Glomeraceae. The first two fungi originated from the Mediterranean Sea sand dunes of the Peloponnese, Greece, and the third was originally found in a tree plantation in Yokohama City, Japan. Phylogenetic analyses of sequences of the 45S nuc rDNA region and the RPB1 gene showed that (i) the three fungi belonged to Glomeraceae; (ii) the first two represented a new genus, here described as Complexispora gen. nov. with C. multistratosa sp. nov. and C. mediterranea sp. nov. and (iii) the third enlarged the monospecific genus Epigeocarpum, as E. japonicum sp. nov.
Explanatory Interactive Machine Learning
Authors: Pfeuffer Nicolas , Baum Lorenz , Stammer Wolfgang , Abdel-Karim Benjamin M. , Schramowski Patrick , Bucher Andreas M. , Hügel Christian , Rohde Gernot , Kersting Kristian , Hinz Oliver
Published: April 2023

The most promising standard machine learning methods can deliver highly accurate classification results, often outperforming standard white-box methods. However, it is hardly possible for humans to fully understand the rationale behind the black-box results, and thus, these powerful methods hamper the creation of new knowledge on the part of humans and the broader acceptance of this technology. Explainable Artificial Intelligence attempts to overcome this problem by making the results more interpretable, while Interactive Machine Learning integrates humans into the process of insight discovery. The paper builds on recent successes in combining these two cutting-edge technologies and proposes how Explanatory Interactive Machine Learning (XIL) is embedded in a generalizable Action Design Research (ADR) process – called XIL-ADR. This approach can be used to analyze data, inspect models, and iteratively improve them. The paper shows the application of this process using the diagnosis of viral pneumonia, e.g., Covid-19, as an illustrative example. By these means, the paper also illustrates how XIL-ADR can help identify shortcomings of standard machine learning projects, gain new insights on the part of the human user, and thereby can help to unlock the full potential of AI-based systems for organizations and research.
Comparative assessment of artificial intelligence (AI)-based algorithms for detection of harmful bloom-forming algae: an eco-environmental approach toward sustainability
Authors: Gaur Ashish , Pant Gaurav , Jalal Anand Singh
Published: April 2023

Organic effluent enrichment in water may selectively promote algal growth, resulting in water pollution and posing a threat to the aquatic ecosystem. Recent harmful algal blooms (HABs) incidents have highlighted information gaps that still exist, as well as the heightened need for early detection technology developments. Although previous research has demonstrated the importance of deep learning in the identification of algal genera, it is still a challenge to identify or to develop the best-suited convolution neural network (CNN) model for effective monitoring of bloom-forming algae. In the present study, efficiency of deep learning models (MobileNet V-2, Visual Geometry Group-16 (VGG-16), AlexNet, and ResNeXt-50) have been evaluated for the classification of 15 bloom-forming algae. To obtain a high level of accuracy, different convolution layers with adaptive moment estimation (Adam), root-mean-square propagation (RMSprop) as optimizers with softmax and rectified linear unit (ReLU) as activation factors have been used. The classification accuracies of 40, 96, 98, and 99% have been achieved for MobileNet V-2, VGG-16, AlexNet, and ResNeXt-50 model, respectively. We believe that the ResNeXt-50 has the potential to identify algae in a variety of situations with high accuracy and in real time, regardless of the underlying hardware. Such studies pave the path for future AI-based cleaner technologies associated with phycological studies for a sustainable future.
Obstacle avoidance of a wheeled robotic swarm using virtual spring-damper mesh
Authors: Wiech Jakub
Published: April 2023

Swarm robotics, in which groups of robots coordinate to achieve a common goal, has the potential to revolutionize a wide range of industries. However, one of the key challenges in developing effective swarm systems is enabling the robots to navigate around obstacles while maintaining cohesion. In this article, the problem of trajectory tracking for a self-organized swarm of wheeled robots in the shape of a regular polygon operating in an environment with obstacles is addressed. The goal is for the swarm to follow a reference point by the geometric center of the swarm, while avoiding collision with obstacles and maintaining a given distance between neighboring robots and the reference point. To solve this problem, a method based on virtual forces that act on each individual robot in the swarm is proposed. These virtual forces are derived from virtual spring-damper connections acting from the obstacles, adjacent robots, and the reference point. The virtual forces allow the robots to dynamically adjust their trajectories to avoid obstacles and maintain the shape of the swarm. The proposed approach is evaluated through simulation and experiment with a swarm of two-wheeled robots. During the experiment the maximum deviation of inter-robot distances was equal to 0.08 m. With the set limit distance to obstacles equal to 0.2 m, from which virtual forces start to push the robot away from the edge of the obstacle, the shortest distance to obstacles was 0.11 m. The results demonstrate the effectiveness of the method in enabling the swarm to accurately follow the reference point while avoiding obstacles and maintaining the desired distances between robots. Overall, the approach represents a step forward in the development of virtual force-based algorithms for obstacle avoidance in swarm robotics.
Digitalisation promotes adoption of soft information in SME credit evaluation: the case of Indian banks
Authors: Hardik Nimbark
Published: April 2023

Small and Medium Enterprises
(SMEs) account for half of the employment in developing economies and are a significant part of their economic growth. In spite of this, SMEs are under-financed by banks, which have been disrupted by financial technology (fintech) firms. This qualitative multi-case study examines how Indian banks are utilising digitalisation, soft information, and Big data to improve SME financing. The participants shared their insights on the way banks adopt digital tools, sources of soft information (e.g., customer and supplier relationships, business plans), and factors that influence the implementation of Big data in the SME credit evaluation process. The major themes include: banks are improving SME financing operations through digitalisation, and IT tools can verify SME soft information. Soft information attributes that emerge from addressing SME information opacity include supplier relationships, customer relationships, business plans, and managerial successions. For SME credit managers, developing partnerships to access publicly available soft information created by industry associations and "online B2B trade platforms" is a high-priority recommendation. To enhance the efficiency of SME financing, banks should obtain the consent of SMEs before they access their private hard information through trade platforms.
Philip Kerr’s 30 Trends in ELT
Authors: Kerr Philip
Published: April 2023

A compact, user-friendly reference book, investigating current trends in ELT. Trends are wide-ranging and include topics such as: plurilingualism, wellbeing, digital literacies, metacognition, flipped learning, gamification, mediation, and critical thinking, amongst others. The book considers how and why each trend has become important in ELT; explores how the trends are reflected in current practices; and evaluates the trends, looking at their relevance to different ELT contexts and their grounding in research.
Augustine's Theology of the Resurrection
Authors: Reisenauer Augustine M.
Published: April 2023

In this volume, Augustine M. Reisenauer, O.P. provides a comprehensive study of Augustine's theology of the resurrection, the human return from death to life. Contextualizing Augustine within the early Church and the intellectual and religious cultures of the late Roman Empire,he interrogates the development of Augustine's thoughts on the historical resurrection of Jesus Christ, the spiritual resurrection of the soul in time, and the fleshly resurrection of the body at the end of time.  Augustine offers profound insights into issues of personal and communal identity, human continuity and transformation, historical and eschatological events, and the God of the resurrection. He also elaborates a biblical paradigm that acknowledges how the resurrected Christ offers an intrinsic participation in his paschal mystery to the souls and bodies of the rest of humanity. Proposing fresh ideas regarding a central topic in Christian theology, Reisenauer's, study also reveals Augustine's defenses of the resurrection against its pagan, philosophical and heretical opponents.
Advanced Practice Nursing im aufsuchenden Setting
Authors: Ledtermann Ivonne
Published: April 2023

Die Gesellschaft wird immer älter. Es kommt zu komplexeren Behandlungs- und Versorgungssituationen. Parallel dazu werden die Forderungen nach einer Versorgung im ambulanten Setting stetig größer. In den letzten Jahren gewinnt das Thema Advanced Practice Nursing (APN) in Deutschland immer mehr an Bedeutung. Diese Arbeit möchte aufzeigen, wie Advanced Practice Nurses (APNs) das Transitional Care Model (TCM) nutzen können.
Implications of Emission Sources and Biosphere Exchange on Temporal Variations of CO2 and δ13C Using Continuous Atmospheric Measurements at Shadnagar (India)
Authors: Pathakoti Mahesh , Kanchana A. L. , Mahalakshmi D. V. , Guha Tania , Raja P. , Nalini K. , Rajan K. S. , Sesha Sai M. V. R. , Dadhwal V. K.
Published: April 2023

Diurnal variation of atmospheric CO2 and its driving factors are studied using high‐precision in situ mixing ratio measurements and stable carbon isotopic CO2 (δ13C‐CO2) for the first time over Shadnagar, a suburban site in India, from November 2018 to October 2019. The annual mean mixing ratios of atmospheric CO2 and δ13C‐CO2 are observed to be 414.76 ± 4.26 ppm and −11.19 ‰ ± 1.63 ‰. Maximum diurnal variability of atmospheric CO2 was observed in summer monsoon (17.30 ± 9.29 ppm), and the minimum was noticed in winter (7.19 ± 0.11 ppm), indicating strong seasonality in diurnal variability of amplitude. To characterize the atmospheric CO2 sources, the Miller‐Tans model was implemented separately using the CO2 and its δ13C‐CO2 isotopic data during day and night. However, a strong source signature of δ13C‐CO2 was observed during the night‐time of summer monsoon with a slope of −37.42‰ ± 0.73‰, obtained using a reduced major axis regression. The identified source indicates possible emissions from fossil fuel combustion. Further, a Lagrangian back trajectory analysis was performed to study the influence of transport on the observed CO2 mixing ratios. The model trajectory confirms the influence of the Indian summer monsoon on the variations of atmospheric CO2 mixing ratios. Our study shows that fossil fuel emissions are one of the major contributors of CO2 in the study location (about ∼2 to 4 ppm) with biogenic fluxes adding a clear seasonality ranging from −8 to 4 ppm.
New Particle Formation Occurrence in the Urban Atmosphere of Beijing During 2013–2020
Authors: Shang Dongjie , Hu Min , Tang Lizi , Fang Xin , Chen Shiyi , Zeng Limin , Guo Song , Zhang Yuanhang , Wu Zhijun
Published: April 2023

New particle formation (NPF) has strong influences on air quality and global climate. However, it was still ambiguous under which atmospheric condition NPF can occur, due to lack of long‐term observation data analysis. The long‐term measurement of NPF was conducted from 2013 to 2020 at PeKing University Urban Atmosphere Environment MonitoRing Station in Beijing, during which strong pollution control measures were conducted. However, the NPF frequency (NPF‐freq) remained stable within 40.4%–48.9% in an average of 42.5%. The occurrence of NPF events was characterized by lower levels of NOx, condensational sink, relative humidity, and higher levels of wind speed and north wind proportion. SO2 may act as one limiting factor only in summer. An H2SO4‐base nucleation indicator, I275K was calculated. It was found that I275K > 243 can separate the NPF and non‐NPF days quite well during the 8 years, with bias at 17%. Accordingly, it was also revealed that the simultaneous control of SO2 and PM2.5 (serving as condensation sink) in Beijing happened to cause the stable level of I275K, as well as the NPF frequency during 2013–2020. The results implicated that along with the reduction of primary emission, the secondary NPF process may become more important in aerosol evolution by its stable frequency, and the precise control of gaseous precursors is required for particle pollution mitigation in the future.
Nutrient-regulated dynamics of chondroprogenitors in the postnatal murine growth plate
Authors: Oichi Takeshi , Kodama Joe , Wilson Kimberly , Tian Hongying , Imamura Kawasawa Yuka , Usami Yu , Oshima Yasushi , Saito Taku , Tanaka Sakae , Iwamoto Masahiro , Otsuru Satoru , Enomoto-Iwamoto Motomi
Published: April 2023

Longitudinal bone growth relies on endochondral ossification in the cartilaginous growth plate, where chondrocytes accumulate and synthesize the matrix scaffold that is replaced by bone. The chondroprogenitors in the resting zone maintain the continuous turnover of chondrocytes in the growth plate. Malnutrition is a leading cause of growth retardation in children; however, after recovery from nutrient deprivation, bone growth is accelerated beyond the normal rate, a phenomenon termed catch-up growth. Although nutritional status is a known regulator of long bone growth, it is largely unknown whether and how chondroprogenitor cells respond to deviations in nutrient availability. Here, using fate-mapping analysis in Axin2CreERT2 mice, we showed that dietary restriction increased the number of Axin2+ chondroprogenitors in the resting zone and simultaneously inhibited their differentiation. Once nutrient deficiency was resolved, the accumulated chondroprogenitor cells immediately restarted differentiation and formed chondrocyte columns, contributing to accelerated growth. Furthermore, we showed that nutrient deprivation reduced the level of phosphorylated Akt in the resting zone and that exogenous IGF-1 restored the phosphorylated Akt level and stimulated differentiation of the pooled chondroprogenitors, decreasing their numbers. Our study of Axin2CreERT2 revealed that nutrient availability regulates the balance between accumulation and differentiation of chondroprogenitors in the growth plate and further demonstrated that IGF-1 partially mediates this regulation by promoting the committed differentiation of chondroprogenitor cells.
TRAP1 S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins
Authors: Papaleo Elena , Tiberti Matteo , Arnaudi Matteo , Pecorari Chiara , Faienza Fiorella , Cantwell Lisa , Degn Kristine , Pacello Francesca , Battistoni Andrea , Lambrughi Matteo , Filomeni Giuseppe
Published: April 2023

S-nitrosylation is a post-translational modification in which nitric oxide (NO) binds to the thiol group of cysteine, generating an S-nitrosothiol (SNO) adduct. S-nitrosylation has different physiological roles, and its alteration has also been linked to a growing list of pathologies, including cancer. SNO can affect the function and stability of different proteins, such as the mitochondrial chaperone TRAP1. Interestingly, the SNO site (C501) of TRAP1 is in the proximity of another cysteine (C527). This feature suggests that the S-nitrosylated C501 could engage in a disulfide bridge with C527 in TRAP1, resembling the well-known ability of S-nitrosylated cysteines to resolve in disulfide bridge with vicinal cysteines. We used enhanced sampling simulations and in-vitro biochemical assays to address the structural mechanisms induced by TRAP1 S-nitrosylation. We showed that the SNO site induces conformational changes in the proximal cysteine and favors conformations suitable for disulfide bridge formation. We explored 4172 known S-nitrosylated proteins using high-throughput structural analyses. Furthermore, we used a coarse-grained model for 44 protein targets to account for protein flexibility. This resulted in the identification of up to 1248 proximal cysteines, which could sense the redox state of the SNO site, opening new perspectives on the biological effects of redox switches. In addition, we devised two bioinformatic workflows (https://github.com/ELELAB/SNO_investigation_pipelines) to identify proximal or vicinal cysteines for a SNO site with accompanying structural annotations. Finally, we analyzed mutations in tumor suppressors or oncogenes in connection with the conformational switch induced by S-nitrosylation. We classified the variants as neutral, stabilizing, or destabilizing for the propensity to be S-nitrosylated and undergo the population-shift mechanism. The methods applied here provide a comprehensive toolkit for future high-throughput studies of new protein candidates, variant classification, and a rich data source for the research community in the NO field.
Immunogenicity and protective efficacy of SARS-CoV-2 mRNA vaccine encoding secreted non-stabilized spike in female mice
Authors: Prompetchara Eakachai , Ketloy Chutitorn , Alameh Mohamad-Gabriel , Tharakhet Kittipan , Kaewpang Papatsara , Yostrerat Nongnaphat , Pitakpolrat Patrawadee , Buranapraditkun Supranee , Manopwisedjaroen Suwimon , Thitithanyanont Arunee , Jongkaewwattana Anan , Hunsawong Taweewan , Im-Erbsin Rawiwan , Reed Matthew , Wijagkanalan Wassana , Patarakul Kanitha , Techawiwattanaboon Teerasit , Palaga Tanapat , Lam Kieu , Heyes James , Weissman Drew , Ruxrungtham Kiat
Published: April 2023

Establishment of an mRNA vaccine platform in low- and middle-income countries (LMICs) is important to enhance vaccine accessibility and ensure future pandemic preparedness. Here, we describe the preclinical studies of “ChulaCov19”, a SARS-CoV-2 mRNA encoding prefusion-unstabilized ectodomain spike protein encapsulated in lipid nanoparticles (LNP). In female BALB/c mice, ChulaCov19 at 0.2, 1, 10, and 30 μg elicits robust neutralizing antibody (NAb) and T cell responses in a dose-dependent relationship. The geometric mean titers (GMTs) of NAb against wild-type (WT, Wuhan-Hu1) virus are 1,280, 11,762, 54,047, and 62,084, respectively. Higher doses induce better cross-NAb against Delta (B.1.617.2) and Omicron (BA.1 and BA.4/5) variants. This elicited immunogenicity is significantly higher than those induced by homologous CoronaVac or AZD1222 vaccination. In a heterologous prime-boost study, ChulaCov19 booster dose generates a 7-fold increase of NAb against Wuhan-Hu1 WT virus and also significantly increases NAb response against Omicron (BA.1 and BA.4/5) when compared to homologous CoronaVac or AZD1222 vaccination. Challenge studies show that ChulaCov19 protects human-ACE-2-expressing female mice from COVID-19 symptoms, prevents viremia and significantly reduces tissue viral load. Moreover, anamnestic NAb response is undetectable in challenge animals. ChulaCov19 is therefore a promising mRNA vaccine candidate either as a primary or boost vaccination and has entered clinical development.