bluuebunny/crossref_metadata_2025 huggingface dataset:
Cutaneous mycobacteriosis caused by Mycobacterium avium subspecies avium in a dog: Clinical findings, histopathological and molecular diagnosis and treatment
Authors: Golchin Diba , Sasani Farhang , Asadian Asma , Jahanbin Negin , Ashrafi Tamai Iradj
Published: January 2024

A 3‐year‐old castrated male Jack Russell Terrier with a history of cholestatic hepatitis was presented with a non‐painful and non‐pruritic, subcutaneous nodule following vaccine injection. The dog was otherwise healthy. The nodule was surgically removed. Upon gross inspection, a firm, glistening and loculated tissue was seen within the panniculus. Histopathologically, extensive pyogranulomatous panniculitis was diagnosed, composed of variably sized lipocyst surrounded by neutrophils and an outer zone of foamy epithelioid macrophages, neutrophils and occasional Langhans form giant cells. Although histopathologic findings were most compatible with mycobacteriosis, other infectious and sterile conditions were considered differential diagnoses. Gram, acid‐fast and periodic acid Schiff staining were negative. However, PCR analyses for mycobacterial rpoB gene and sequencing revealed infection with Mycobacterium avium subsp. avium. Empirical treatment was avoided through the 3‐week course of histopathological and molecular investigations. Considering that there were no newly formed cutaneous masses, marbofloxacin (2 mg/kg, PO q24h) was administered for 2 weeks, and clarithromycin was avoided due to its potential cholestatic hepatitis adverse effects. Eight months following surgery, there are no new or relapsing cutaneous lesions or disease‐specific complications. This suggests that marbofloxacin monotherapy may be sufficient in immunocompetent dogs with early detection of localized cutaneous mycobacteriosis lacking lymph node or organ involvement.
Seroprevalence of small ruminant brucellosis in the state of Qatar
Authors: Alhussain Hashim , Gawish Ahmed , Zughaier Susu , Al‐Zeyara Abdulaziz M. , Yassine Hadi M. , Al Thani Asmaa , Eltai Nahla O.
Published: January 2024

Background

Brucellosis is one of the most important zoonotic diseases worldwide, with a significant economic and health burden. The disease is endemic in many regions around the world. Data regarding the disease in the Arabic Gulf region is scarce, and a limited number of studies have been conducted in Qatar. This study is the first to investigate the seroprevalence of small ruminant brucellosis in the state of Qatar.

Methods

The country was divided into three zones based on animal population (high, medium and low). A total of 494 blood samples from 57 small ruminant flocks were randomly collected from the three zones. Rose Bengal and competitive enzyme‐linked immunosorbent assay were used to investigate the apparent and true seroprevalence at both the animal and flock levels. A regression model was used to investigate the potential risk factors, including geographic zone, sex and age.

Results

At the animal level, the overall (sheep and goat) apparent and true seroprevalence were 9.6% (95% confidence interval [95% CI]: 7.3–12.5) and 8.4% (95% CI: 5.9–11.5), respectively. In sheep, the apparent seroprevalence was 16.7% (95% CI: 12.5–21.8), and the true seroprevalence was 16.1% (95% CI: 11.6–21.7), whereas in goats, the apparent seroprevalence was 2.4% (95% CI: 1.1–5.2), and the true seroprevalence was 0.7% (95% CI: −0.7 to 3.7). At the flock level, overall, apparent sheep and goat seroprevalence were 19.3% (95% CI: 11.1–31.3), 30.0% (95% CI: 16.1–49.8) and 7.4% (95% CI: 2.1–23.4) and true seroprevalence was 18.9% (95% CI: 10.1–31.9), 30.5% (95% CI: 16.1–49.8) and 6.1% (95% CI: 0.3–23.3) respectively. Univariable regression analysis revealed age as the only significant risk factor in the sampled population.

Conclusions

Brucella appears to be endemic to small ruminants in Qatar. The findings of this study provide baseline data regarding small ruminant brucellosis in Qatar and will aid in plans to control and eradicate the disease.
Water‐based technologies for improving water quality at the point of use: A review
Authors: Shayo Godfrey M. , Elimbinzi Elianaso , Shao Godlisten N.
Published: January 2024

Water safety concerns are increasing tremendously as a result of the rising population and environmental pollution. As a result, viable water treatment approaches need to be designed to meet the water consumption demands of the population, particularly in developing countries. The recent technological advances in water treatment and purification are well articulated in this review. The efficiency of the materials used for purification and their affordability for people living in rural and remote settlements in various parts of the world have been discussed. Water treatment techniques prior to the rapid advancement of science and technology included a variety of strategies such as coagulation/flocculation, filtration, disinfection, flotation and pH correction. The use of nanotechnology in water treatment and purification has modernized the purification process. Therefore, efficient removal of microbes such as bacteria and viruses are exquisitely accomplished. These technologies may include membrane filtration, ultraviolet irradiation, advanced oxidation ion‐exchange and biological filtration technologies. Thus, nanotechnology allows for the fabrication of less expensive systems, allowing even low‐income people to benefit from it. Most developing countries find these technologies particularly valuable because access to clean and safe water for drinking and residential needs is critical. This is because access to municipal water supplies is also difficult.

This article is categorized under:

Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials

Diagnostic Tools > In Vivo Nanodiagnostics and Imaging
Frame potential of Brownian SYK model of Majorana and Dirac fermions
Authors: Tiutiakina Anastasiia , De Luca Andrea , De Nardis Jacopo
Published: January 2024

Abstract

We consider the Brownian SYK, i.e. a system of N Majorana (Dirac) fermions with a white-noise q-body interaction term. We focus on the dynamics of the Frame potentials, a measure of the scrambling and chaos, given by the moments of the overlap between two independent realisations of the model. By means of a Keldysh path-integral formalism, we compute its early and late-time value. We show that, for q > 2, the late time path integral saddle point correctly reproduces the saturation to the value of the Haar frame potential. On the contrary, for q = 2, the model is quadratic and consistently we observe saturation to the Haar value in the restricted space of Gaussian states (Gaussian Haar). The latter is characterised by larger system size corrections that we correctly capture by counting the Goldstone modes of the Keldysh saddle point. Finally, in the case of Dirac fermions, we highlight and resolve the role of the global U(1) symmetry.
Annular type surfaces with fixed boundary and with prescribed, almost constant mean curvature
Authors: Caldiroli Paolo , Cora Gabriele , Iacopetti Alessandro
Published: January 2024

We prove existence and nonexistence results for annular type parametric surfaces with prescribed, almost constant mean curvature, characterized as normal graphs of compact portions of unduloids or nodoids in $${\mathbb {R}}^{3}$$

R

3

, and whose boundary consists of two coaxial circles of the same radius.
Gestaltungs- und Evaluationsmöglichkeiten von Multimediaanwendungen zur Unterstützung der Betreuung von Menschen mit leichter Demenz
Authors: von Bosse Alexa , Bejan Alexander , Wessel Max , Kunze Christophe
Published: January 2024

Hintergrund

Zur kognitiv-körperlichen Aktivierung von Menschen mit Demenz (MMD) im stationären Setting stehen vielfältige, zielgruppenspezifisch konzipierte touchbasierte Multimedia-Anwendungen zur Verfügung, die auch tatsächlich in der Praxis genutzt werden. Im Vergleich dazu ist der Einsatz vergleichbarer Anwendungen in der Häuslichkeit bislang gering ausgeprägt.

Ziel und Methodik

Die vorliegende Studie untersucht anhand von 11 leitfadengestützten Expert*inneninterviews sowohl Gestaltungsoptionen und Anforderungen an Anwendungsinhalte als auch Anforderungen an Studiendesigns zu Wirksamkeitsnachweisen touchbasierter Multimedia-Anwendungen für MMD und ihre pflegenden Angehörigen (PA).

Ergebnisse

Es zeigt sich eine große Übereinstimmung bezüglich allgemeiner Anforderungskriterien an touchbasierte Multimedia-Anwendungen – die Akzeptanz ist in hohem Maße von Nutzungskompetenzen, Nutzungspraktiken, Erfahrungen sowie Anreizstrukturen abhängig. Auf der anderen Seite liegen heterogene Meinungen zur inhaltlich-strukturellen Ausgestaltung touchbasierter Multimedia-Anwendungen für MMD vor. Lebensqualität wird als elementarer Evaluationsparameter von Multimedia-Anwendungen genannt.

Diskussion

Individuell stark variierende Lebensumstände von MMD und ihren PA sowie mangelnde Zugangsmöglichkeiten und fehlende Passgenauigkeit der Multimedia-Anwendungen können ursächlich für ihren bislang geringen Einsatz insbesondere in der Häuslichkeit sein. Tagesabhängige Leistungsfähigkeiten und individuelle Krankheitsverläufe stellen besondere Anforderungen an die wissenschaftliche Evaluation und an Wirksamkeitsnachweise touchbasierter Multimedia-Anwendungen dar.
Occupational injuries in orthopedic and trauma surgeons in Austria
Authors: Clar Clemens , Koutp Amir , Leithner Andreas , Leitner Lukas , Puchwein Paul , Vielgut Ines , Sadoghi Patrick
Published: January 2024

Background

The aim of this study was to investigate the frequency and type of injuries during the career of orthopedic and trauma surgeons in Austria. The hypothesis was that the percentage of occupational injuries among orthopedic and trauma surgeons aligns with the incidence reported in the United States, thus indicating the need for a workplace prevention program.

Methods

A web-based survey was created to collect all necessary data and was sent to all orthopedic and trauma surgeons in Austria via e-mail. Relevant parameters included the surgeons’ age, work experience, severity of pain, type of injury, and current pain. Descriptive and explorative statistical analysis was performed.

Results

A web-based survey was sent to 1122 board-certified orthopedic surgeons and residents in Austria via e-mail. In total, the response rate was 135 (12%). Seventy-two surgeons (54%) had suffered from one or more occupational injuries during their career. We detected a significant raise of occupational injuries related to the work life duration in which operations were performed and the prevalence of injuries. Most injuries of surgeons were reported between 21 and 30 years of their professional life. According to the frequency at different locations, the distribution in descending order was 25% with injuries of the hand, 22% of finger(s), 12% of the foot, 10% of the spine, 2% of the neck, 3% of the head, and 2% of the abdomen. A causality of incapacity to work through injuries at the workplace was given as 4%. Four percent stated a sick leave of at least 3 weeks. In 7% of the facilities, there was no optimization of preventive measures following an occupational injury. We found no correlation of injuries and resident status.

Conclusion

Orthopedic surgeons in Austria show a high incidence of occupational injuries in line with the findings of colleagues from the United States. The impact on the health system consists of absenteeism in the workplace of highly specialized health service providers as well as the incapacity to work of a high quality, highly trained workforce of at least 4%. With more preventive measures and more attention and care in the rehabilitation phase after such injuries, a positive effect could be achieved. We believe that residents should be specifically trained on how to avoid such injuries.
The m6A demethylase FTO targets POLQ to promote ccRCC cell proliferation and genome stability maintenance
Authors: He Yichen , Chen Yimeng , Li Zhengsheng , Wu Changping
Published: January 2024

Background and aim

As the first identified m6A demethylase, FTO has been implicated in the progression of various cancers. However, the specific mechanism of FTO in clear cell renal cell carcinoma (ccRCC) remains incompletely understood. In this study, we aimed to explore the potential molecular mechanisms influencing the progression of ccRCC.

Methods

We initially assessed the expression of FTO in tumor and adjacent tissues using TCGA database, RT-qPCR, and Western blot. We then conducted CCK-8, cell cycle analysis, and colony formation assay to investigate the impact of FTO on ccRCC cell proliferation. MeRIP-seq and RNA-seq were employed to identify potential downstream targets of FTO in ccRCC, and these findings were further validated through dual-luciferase reporter assays and MeRIP-qPCR. Then, DNA damage and cell death were assessed separately through gammaH2AX immunofluorescence detection and the LIVE/DEAD Fixable Dead Cell Stain assay, respectively. Subsequently, we identified downstream pathways influenced by FTO's regulation of POLQ through TCGA database analysis and GSEA enrichment analysis. Validation was carried out through Western blot.

Results

FTO is highly expressed in ccRCC tissues and cell lines. Furthermore, ROC curve demonstrates that FTO contributes to the diagnosis of ccRCC. FTO modulates m6A modification, consequently influencing the expression of POLQ, thus facilitating cell proliferation and maintaining genome stability in ccRCC.

Conclusion

FTO could potentially serve as a diagnostic marker for ccRCC. FTO promotes the progression of ccRCC by regulating m6A modification, making the inhibition of FTO a potential novel therapeutic strategy in ccRCC.
Prognosis and immunotherapy response prediction based on M2 macrophage-related genes in colon cancer
Authors: Xu Xiaochen , Zhang Xinwen , Kou Ruilong , Liu Yihao , Chen Siqi , Li Zuguo , Jian Zhiyuan , wang Zhenran
Published: January 2024

Background

M2 macrophage were revealed to play a crucial role in immune evasion and immunotherapies. This study aims to explore the potential significance of M2 macrophage-related genes in colon adenocarcinoma (COAD) by analysizing the transcriptome data in a comprehensive way.

Methods

We collected RNA-sequencing (RNA-seq) data of COAD from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) databases. We calculated the immune infiltration scores of every sample using CIBERSORT algorithm. Through weighted gene co-expression network analysis (WGCNA), we picked out M2 macrophage-related genes. With these genes we screened out prognosis related genes which were utilized to construct a signature to assess the prognosis of patients. To extend the potential application of the signature, we also calculated the correlations with immune infiltration. Finally, we applied techniques such as quantitative reverse transcription polymerase chain reaction (qRT–PCR) and immunoblotting (Western Blotting) to validate the RNF32 gene in cellular in vitro assays.

Results

Seven M2 macrophage-related genes signature was constructed, which was an excellent prognostic predictor in two independent groups. The high-risk group showed lower immune infiltration and poorer response to immunotherapies than those of the low-risk group. The cell vitro experiments showed that the expression level of RNF32 was upregulated in colon cancer cell lines compared with normal cell lines. Moreover, we found that RNF32 may promote the proliferation, migration and invasion of cancer cells in vitro by inhibiting apoptosis.

Conclusion

A novel M2 macrophage-related gene signature affects the prognosis and immune characteristics of colon cancer.
Prediction of positive pulmonary nodules based on machine learning algorithm combined with central carbon metabolism data
Authors: Liu Jian-jun , Shen Wen-bin , Qin Qi-rong , Li Jian-wei , Li Xue , Liu Meng-yu , Hu Wen-lei , Wu Yue-yang , Huang Fen
Published: January 2024

Background

Lung cancer causes a huge disease burden, and early detection of positive pulmonary nodules (PPNs) as an early sign of lung cancer is extremely important for effective intervention. It is necessary to develop PPNs risk recognizer based on machine learning algorithm combined with central carbon metabolomics.

Methods

The study included 2248 participants at high risk for lung cancer from the Ma'anshan Community Lung Cancer Screening cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to screen 18 central carbon-related metabolites in plasma, recursive feature elimination (RFE) was used to select all 42 features, followed by five machine learning algorithms for model development. The performance of the model was evaluated using area under the receiver operator characteristic curve (AUC), accuracy, precision, recall, and F1 scores. In addition, SHapley Additive exPlanations (SHAP) was performed to assess the interpretability of the final selected model and to gain insight into the impact of features on the predicted results.

Results

Finally, the two prediction models based on the random forest (RF) algorithm performed best, with AUC values of 0.87 and 0.83, respectively, better than other models. We found that homogentisic acid, fumaric acid, maleic acid, hippuric acid, gluconic acid, and succinic acid played a significant role in both PPNs prediction model and NPNs vs PPNs model, while 2-oxadipic acid only played a role in the former model and phosphopyruvate only played a role in the NPNs vs PPNs model. This model demonstrates the potential of central carbon metabolism for PPNs risk prediction and identification.

Conclusion

We developed a series of predictive models for PPNs, which can help in the early detection of PPNs and thus reduce the risk of lung cancer.
Auf dem Weg zum Fahrradland – Barrieren von Nichtradfahrer*innen identifizieren und überwinden
Authors: Popp Monika , Rau Henrike , Mahne-Bieder Johannes
Published: January 2024

Die Steigerung des Fahrradverkehrs wird als wichtiger Baustein bei der Transformation hin zu einer nachhaltigen Mobilität gesehen. Der Nationale Radverkehrsplan 3.0 setzt hier unter dem Titel „Fahrradland Deutschland 2030“ ein deutliches Ziel. Die bisherige Fahrradförderung zeigt bisher allerdings nur punktuelle Erfolge: Der durchschnittliche Anteil der Fahrten mit dem Fahrrad ist in Deutschland in den letzten 20 Jahren kaum gestiegen und insbesondere der Anteil der Nichtradfahrer*innen konnte nicht reduziert werden. Im Vergleich zu sogenannten Fahrradnationen wie den Niederlanden ist der Anteil der Personen in Deutschland, die nur selten oder gar nicht Rad fahren, außerdem sehr hoch, was ein klares Hemmnis für die Mobilitätswende darstellt. Das Projekt RadAktiv hat deswegen Radfahrer*innen und Nichtradfahrer*innen systematisch verglichen und Barrieren der Radnutzung identifiziert. Die Studie basiert auf qualitativen Interviews sowie einer deutschlandweiten repräsentativen Befragung (n = 5002). Die größten Unterschiede zwischen Radfahrer*innen und Nichtradfahrer*innen wurden im Bereich der Mobilitätssozialisation und in der Einschätzung der Alltagstauglichkeit des Fahrrads als Verkehrsmittel identifiziert. Außerdem wurde eine Klassifizierung der Nichtradfahrer*innen vorgenommen, die anhand der Aktivierbarkeit drei Typen und ihre spezifischen Barrieren beschreibt: Beinahe-Radfahrer*innen, Radskeptiker*innen und Radverweigerer*innen. Aus den Ergebnissen wurden typspezifische Maßnahmen zur Aktivierung von Nichtradfahrer*innen abgeleitet. Neben Infrastrukturmaßnahmen, die bereits im Fokus vieler Förderanstrengungen stehen, müssen dabei zukünftig auch soziale und kulturelle Gründe für das Nichtradfahren stärkere Berücksichtigung finden. Eine zielgruppengerechte und typenspezifische Kommunikation bezüglich der Vorteile des Fahrrads, die Stärkung einer fahrradfreundlichen Mobilitätskultur sowie die explizite Anerkennung der lebensweltlichen Bedingungen und Erfahrungen verschiedener Typen von Nichtradfahrer*innen stellen dabei vielversprechende Ansätze dar.
Basic method for water detection in LiPF6-based electrolytes
Authors: Šimek Antonín , Kazda Tomáš , Báňa Jiří , Čech Ondřej
Published: January 2024

This paper investigates the effect of water content on lithium-ion battery electrolytes with particular emphasis on the degradation of lithium hexafluorophosphate, a commonly used salt in commercial electrolytes. The study addresses various degradation mechanisms caused by water in a battery system. In addition, the research utilizes electrochemical techniques to detect water and associated changes in electrochemical performance of the cell. The electrochemical water detection method investigated is very fast. The lower detection limit was not tested, but contamination of 250 ppm can be reliably detected. It can be used, for example, in experimental research to determine the purity and quality of the electrolyte used.

Graphical abstract
A multi-method investigation of the permeability structure of brittle fault zones with ductile precursors in crystalline rock
Authors: Osten Julian , Schaber Tom , Gaus Garri , Hamdi Pooya , Amann Florian , Achtziger-Zupančič Peter
Published: January 2024

Brittle faults and fault zones are among the most hydraulically active elements in predominantly impermeable crystalline host rock. They pose a significant challenge to underground infrastructure like nuclear waste repositories. Brittle fault zones frequently occur along pre-existing ductile shear zones as they introduce weakness planes in the rock.

Four brittle fault zones of ductile origin were analyzed in the Rotondo Granite at the “BedrettoLab” in the Swiss Central Alps. Scanline mapping, rock sampling and permeability measurements using three different methods provide detailed insights into the heterogeneous fault zone architecture and hydrogeology. Average intact rock permeability is in the range of 10−19 to 10−17 m2. Fluid flow is channeled into single open or partially mineralized fractures of, at point-scale, up to 10−14 m2, demonstrated by selective gas probe permeameter measurements and borehole hydraulic testing. Reduced permeabilities have been measured in close proximity to these permeable features, indicating alteration of and around the fracture walls.
Distinguishing between Crohn’s disease and ulcerative colitis using deep learning models with interpretability
Authors: Maurício José , Domingues Inês
Published: January 2024

Crohn’s disease and ulcerative colitis are two chronic diseases that cause inflammation in the tissues of the entire gastrointestinal tract and are described by the term inflammatory bowel disease. Gastroenterologists find it difficult to evaluate endoscopic images to recognise the characteristics of the two chronic diseases. Therefore, this work aims to build a dataset with images of Crohn’s disease and ulcerative colitis (collected from the public datasets LIMUC, HyperKvasir and CrohnIPI) and train deep learning models (five CNNs and six ViTs) to develop a tool capable of helping doctors to distinguish the type of inflammatory bowel disease. In addition, as these architectures will be too heavy to work in a hospital context, in this work, we are looking to use knowledge distillation to create lighter and simpler architectures with the same precision as the pre-trained architectures used in this study. During this process, it is important to evaluate and interpret the pre-trained architectures before the distillation process, and the architectures resulting from knowledge distillation to ensure that we can maintain performance and that the information learnt by both architectures are similar. It is concluded that is possible to reduce 25x the number of parameters while maintaining good performance and reducing the inference time by 5.32 s. Allied with this, through the interpretability of the models was concluded that both before and after the knowledge distillation are possible to identify ulcers, bleeding situations, and lesions caused by the inflammation of the disease.
Fully immersive learning with virtual reality for assessing students in art history
Authors: Cecotti Hubert , Huisinga Laura , Peláez Luis Gordo
Published: January 2024

Immersive learning systems using consumer grade headsets for virtual reality (VR) software can now reach the classroom. VR represents an important step toward situated learning for bringing realistic experiences to show to students different types of content the way it appears in real life. With the three-dimensional effect, it adds an immersive dimension that can bring the student into a unique environment that is directly connected to the learning content. While VR experiences can be helpful in educational settings, they must satisfy the learning objectives of the course and the specific needs of the students. In this paper, we propose a customizable VR application for displaying paintings for their analysis, and their associated questions designed for instructors in art history. To improve the accessibility and adaptivity to instructors and specific learning materials, we propose the definition of the paintings’ characteristics and the questionnaires associated with the paintings in the JSON open-standard file format, facilitating application changes without any prior programming knowledge. We compare the proposed VR modality with a web-based application on a computer desktop with 35 undergraduate students with art history experience. In both modalities, we assess the workload and usability; the VR sickness symptoms and the motivation in the VR condition. The results indicate better usability and lower workload with the VR condition. While there are no differences in terms of students’ performance for answering the questions, 77% of students prefer the VR condition. The Reduced Instructional Materials Motivation Survey shows a high motivation in the student population. Finally, the system evaluation supports the conclusion that the proposed VR system can be deployed in the art history classroom as the system has a high usability and medium workload.
Allometric equations to calculate living and dead fuel loads in Mediterranean species
Authors: Deltell Leyre , Santana Victor Manuel , Jaime Baeza M.
Published: January 2024

Determining the structure and fuel load is key to know the flammability of vegetation in the Mediterranean Basin where forest fires are frequent. Determine which plant structural variable is best related to living and dead fuel to develop allometric equations in nine species in the Western Mediterranean Basin. In the east of the Iberian Peninsula (Valencia Province), we measured four structural variables (basal stem diameter, height, maximum diameter and perpendicular diameter) that were related, by means of allometric equations, to the living and dead fuel separated into different size classes. We also analyze fuel changes across developmental states of the studied species, and the vertical distribution of dead fuel. General equations that consider all development states can be used to determine living fuel. However to obtain dead fuel, we recommend using specific equations for each development state and fuel fraction for better accuracy. The basal stem diameter was the best structural variable in almost all cases for estimating fuel in the studied species. Dead fuel load throughout species’ ontological development is a key factor to manage Mediterranean plant communities.
Characterizing Socioecological Markers of Differentiated HIV Risk Among Men Who Have Sex with Men in Indonesia
Authors: Nevendorff Laura , Pedrana Alisa , Bourne Adam , Traeger Michael , Sindunata Eric , Reswana Wawa A. , Alharbi Rosidin M. , Stoové Mark
Published: January 2024

HIV prevention programs typically focus on changing individuals’ risk behaviors, often without considering the socioecological factors that can moderate this risk. We characterized HIV risk among men who have sex with men (MSM) in Indonesia (n = 1314) using latent class analysis and used multinomial logistic regression to identify latent class relationships with demographics, social/sexual networks, and community-level socioecological indicators of HIV risk. Three HIV risk latent classes were identified—“Sexually Moderate” (n = 333), “Sexual Explorative” (n = 575), and “Navigating Complexities” (n = 406). Using “Sexually Moderate” (lowest risk) as the reference group, MSM in the “Sexual Explorative” class had additional social/sexual network-level risks (meeting partner(s) using both online and offline methods [RR = 3.8; 95%CI 1.7–8.6] or general social media and gay-specific online platforms [RR = 2.6; 95%CI 1.9–3.6] to meet partners, group sex [RR = 10.9; 95%CI 4.5–25.4], transactional sex [RR = 1.6; 95%CI 1.2–2.2]), and community-level risks (experiencing homosexual-related assaults [RR = 1.4; 95%CI 1.1–1.9]). MSM in the “Navigating Complexities” class had additional social/sexual network-level risks (low social support [RR = 1.6; 95%CI 1.1–2.5], less disclosure of their sexuality [RR = 1.4; 95%CI 1.0–1.9]) and community-level risks (higher internalized homonegativity scores [RR = 1.2; 95%CI 1.1–1.4], ever experiencing homosexual-related assaults [RR = 1.4:95%CI 1.1–1.9], less exposure to HIV/STI health promotion [RR = 0.7; 95%CI 0.5–0.9], attending STI-related services in the past 6 months [RR = 0.6; 95%CI 0.4–0.8]). Co-occurring individual and socioecological risk recommend holistic HIV prevention strategies tailored to consider the social and structural conditions of MSM in Indonesia are needed.
Finding the input features that reduce the entropy of a neural network’s prediction
Authors: Amanova Narbota , Martin Jörg , Elster Clemens
Published: January 2024

In deep learning-based image classification, the entropy of a neural network’s output is often taken as a measure of its uncertainty. We introduce an explainability method that identifies those features in the input that impact most this uncertainty. Learning the corresponding features by straightforward backpropagation typically leads to results that are hard to interpret. We propose an extension of the recently proposed oriented, modified integrated gradients (OMIG) technique as an alternative to produce perturbations of the input that have a visual quality comparable to explainability methods from the literature but marks features that have a substantially higher impact on the entropy. The potential benefits of the modified OMIG method are demonstrated by comparison with current state-of-the-art explainability methods on several popular databases. In addition to a qualitative analysis of explainability results, we propose a metric for their quantitative comparison, which evaluates the impact of identified features on the entropy of a prediction.
Genotype-Environment Interaction in ADHD: Genetic Predisposition Determines the Extent to Which Environmental Influences Explain Variability in the Symptom Dimensions Hyperactivity and Inattention
Authors: Schwabe Inga , Jović Miljan , Rimfeld Kaili , Allegrini Andrea G. , van den Berg Stéphanie M.
Published: January 2024

Although earlier research has shown that individual differences on the spectrum of attention deficit hyperactivity disorder (ADHD) are highly heritable, emerging evidence suggests that symptoms are associated with complex interactions between genes and environmental influences. This study investigated whether a genetic predisposition [Note that the term ‘genetic predisposition’ was used in this manuscript to refer to an estimate based on twin modeling (an individual’s score on the latent trait that resembles additive genetic influences) in the particular population being examined.] for the symptom dimensions hyperactivity and inattention determines the extent to which unique-environmental influences explain variability in these symptoms. To this purpose, we analysed a sample drawn from the Twins Early Development Study (TEDS) that consisted of item-level scores of 2168 16-year-old twin pairs who completed both the Strengths and Difficulties Questionnaire (SDQ; Goodman, in J Child Psychol Psychiatry 38:581–586, 1997) and the Strength and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN; Swanson, in Paper presented at the meeting of the American Psychological Association, Los Angeles, 1981) questionnaire. To maximize the psychometric information to measure ADHD symptoms, psychometric analyses were performed to investigate whether the items from the two questionnaires could be combined to form two longer subscales. In the estimation of genotype-environment interaction, we corrected for error variance heterogeneity in the measurement of ADHD symptoms through the application of item response theory (IRT) measurement models. A positive interaction was found for both hyperactivity (e.g., $${\beta }_{1}$$

β
1

= 2.20 with 95% highest posterior density interval equal to [1.79;2.65] and effect size equal to 3.00) and inattention (e.g., $${\beta }_{1}$$

β
1

= 2.16 with 95% highest posterior density interval equal to [1.56;2.79] and effect size equal to 3.07). These results indicate that unique-environmental influences were more important in creating individual differences in both hyperactivity and inattention for twins with a genetic predisposition for these symptoms than for twins without such a predisposition.
m6A modification mediates SLC3A2/SLC7A5 translation in 3-methylcholanthrene-induced uroepithelial transformation
Authors: Liu Bixia , Lv Yifan , Hu Wenyu , Huang Yapeng , Ying Xiaoling , Chen Cong , Zhang Haiqing , Ji Weidong
Published: January 2024

3-Methylcholanthracene (3-MC) is one of the most carcinogenic polycyclic aromatic hydrocarbons (PAHs). Long-term exposure to PAHs has been thought of as an important factor in urothelial tumorigenesis. N6-methyladenosine (m6A) exists widely in eukaryotic organisms and regulates the expression level of specific genes by regulating mRNA stability, translation efficiency, and nuclear export efficiency. Currently, the potential molecular mechanisms that regulate m6A modification for 3-MC carcinogenesis remain unclear. Here, we profiled mRNA, m6A, translation and protein level using “-omics” methodologies, including transcriptomes, m6A profile, translatomes, and proteomics in 3-MC-transformed urothelial cells and control cells. The key molecules SLC3A2/SLC7A5 were screened and identified in 3-MC-induced uroepithelial transformation. Moreover, SLC7A5/SLC3A2 promoted uroepithelial cells malignant phenotype in vitro and in vivo. Mechanically, METTL3 and ALKBH5 mediated m6A modification of SLC3A2/SLC7A5 mRNA in 3-MC-induced uroepithelial transformation by upregulating the translation of SLC3A2/SLC7A5. Furthermore, programmable m6A modification of SLC3A2/SLC7A5 mRNA affected the expression of its proteins. Taken together, our results revealed that the m6A modification-mediated SLC3A2/SLC7A5 translation promoted 3-MC-induced uroepithelial transformation, suggesting that targeting m6A modification of SLC3A2/SLC7A5 may be a potential therapeutic strategy for bladder cancer related to PAHs.
Schrödinger Cats and Quantum Complementarity
Authors: Maccone Lorenzo
Published: January 2024

Complementarity tells us we cannot know precisely the values of all the properties of a quantum object at the same time: the precise determination of one property implies that the value of some other (complementary) property is undefined. E.g. the precise knowledge of the position of a particle implies that its momentum is undefined. Here we show that a Schrödinger cat has a well defined value of a property that is complementary to its “being dead or alive” property. Then, thanks to complementarity, it has an undefined value of the property “being dead or alive”. In other words, the cat paradox is explained through quantum complementarity: of its many complementary properties, any quantum system, such as a cat, can have a well defined value only of one at a time. Schrödinger’s cat has a definite value of a property which is complementary to “being dead or alive”, so it is neither dead nor alive. Figuratively one can say it is both dead and alive. While this interpretation only uses textbook concepts (the Copenhagen interpretation), apparently it has never explicitly appeared in the literature. We detail how to build an Arduino based simulation of Schrödinger’s experiment based on these concepts for science outreach events.
Visualization of Digital Transformation Initiatives Elements through ArchiMate Viewpoints
Authors: Bogea Gomes Silvia , Santoro Flavia Maria , da Silva Miguel Mira , Iacob Maria-Eugenia
Published: January 2024

Digital transformation stems from a mix of personal and corporate IT environments and involves integrating digital technologies and business processes in a digital economy. As such, organizations expect that digital transformation improves performance, increases their reach, and ensures better business results. However, there is still a lack of (i) conceptual models to provide an accurate representation of the digital transformation elements; and (ii) standard visualizations of such elements to specific stakeholders. In a previous work, a reference model to support digital transformation initiatives using ArchiMate was proposed. In this paper, we address the second part of this problem regarding the need for specific visualizations. We followed the Design Science Research approach to learn how to identify the needs of the stakeholders, extending and improving the reference model through the design of a set of architectural viewpoints. We used the well-known ArchiSurance case to demonstrate the application of the viewpoints and semi-structured interviews to evaluate the proposal, providing insights to the discussion of the results obtained.
State-Dependent Maximum Entropy Reinforcement Learning for Robot Long-Horizon Task Learning
Authors: Zheng Deshuai , Yan Jin , Xue Tao , Liu Yong
Published: January 2024

Task-oriented robot learning has shown significant potential with the development of Reinforcement Learning (RL) algorithms. However, the learning of long-horizon tasks for robots remains a formidable challenge due to the inherent complexity of tasks, typically comprising multiple diverse stages. Universal RL algorithms commonly encounter issues such as slow convergence or even failure to converge altogether when applied to such tasks. The reasons behind these challenges lie in the local optima trap or redundant exploration during the new stages or the junction of two continuous stages. To address these challenges, we propose a novel state-dependent maximum entropy (SDME) reinforcement learning algorithm. This algorithm effectively balances the trade-off between exploration and exploitation around three kinds of critical states arising from the unique nature of long-horizon tasks. We conducted experiments within an open-source simulation environment, focusing on two representative long-horizon tasks. The proposed SDME algorithm exhibits faster and more stable learning capabilities, requiring merely one-third of the number of learning samples necessary for baseline approaches. Furthermore, we assess the generalization ability of our method under randomly initialized conditions, and the results show that the success rate of the SDME algorithm is nearly twice that of the baselines. Our code will be available at https://github.com/Peter-zds/SDME.
Online Capability Based Task Allocation of Cooperative Manipulators
Authors: Patra Keshab , Sinha Arpita , Guha Anirban
Published: January 2024

The cooperative manipulator group can accomplish complex and heavy payload tasks of object manipulation and transportation compared to a single manipulator. Effective coordination is crucial for cooperative task accomplishments. Multi-manipulator task distribution is highly complex because of the varying dynamic capabilities of the manipulators. We have introduced a novel fastest technique to quantify the dynamic task capability of the cooperative manipulator by scalar quantity and allocate the task accordingly. The scalar quantity determines the capability of applying an external wrench by end effector (EE) in line with the required wrench at the center of mass of the manipulating object. This quantity helps to diminish tracking errors in object manipulations or transportation and actuator saturation avoidance. The task distribution among the members is in proportion to their computed dynamic capability to ensure equal priority to the individual manipulators. The proposed task distribution formulation ensures the minimum magnitude of wrench interaction at the grasp point and the minimum internal wrench build-up in the object. Several physical simulation results assure trajectory tracking performance with the proposed task capability metric. The same metric aids in identifying the least capable manipulator, rearranging members for better performance, and deciding the required number of manipulators in the manipulator group.
Modelling, Analysis, and Control of OmniMorph: an Omnidirectional Morphing Multi-rotor UAV
Authors: Aboudorra Youssef , Gabellieri Chiara , Brantjes Ralph , Sablé Quentin , Franchi Antonio
Published: January 2024

This paper introduces for the first time the design, modelling, and control of a novel morphing multi-rotor Unmanned Aerial Vehicle (UAV) that we call the OmniMorph. The morphing ability allows the selection of the configuration that optimizes energy consumption while ensuring the needed maneuverability for the required task. The most energy-efficient uni-directional thrust (UDT) configuration can be used, e.g., during standard point-to-point displacements. Fully-actuated (FA) and omnidirectional (OD) configurations can be instead used for full pose tracking, such as, e.g., constant attitude horizontal motions and full rotations on the spot, and for full wrench 6D interaction control and 6D disturbance rejection. Morphing is obtained using a single servomotor, allowing possible minimization of weight, costs, and maintenance complexity. The actuation properties are studied, and an optimal controller that compromises between performance and control effort is proposed and validated in realistic simulations. Preliminary tests on the prototype are presented to assess the propellers’ mutual aerodynamic interference.
Thermal dependence on electrical characteristics of Au/(PVC:Sm2O3)/n-Si structure
Authors: Badali Yosef , Altan Hayati , Altındal Semsettin
Published: January 2024

In this study, we investigated the current–voltage (I–V) characteristics of Au/n-Si structure with an interfacial layer of Samarium Oxide (Sm2O3) nanoparticles (NPs) in polyvinyl chloride (PVC) matrix within a temperature range of 80–320 K. Applying the thermionic emission (TE) theory, essential electrical parameters such as reverse saturation current (I0), ideality factor (n), zero bias barrier height (ΦB0), series resistance (Rs), and rectification rate (RR) were carefully derived from the I–V data. The mean values of BH and Richardson constant obtained from the modified Richardson plot were determined to be 0.730 eV and 111.4 A/(cmK)2, respectively. Remarkably, this A* value closely matches its theoretical counterpart for n-type Si. Thus, our findings successfully highlight the effectiveness of the thermionic emission (TE) mechanism with the Gaussian distribution of BHs in explaining the I-V-T characteristics of the fabricated Schottky structure, shedding light on the intricate interplay between temperature and diode behavior. These insights offer valuable guidance for designing and optimizing thermal-sensitive devices based on this innovative structure.
Daily Idea Generation and Employee Creative Performance: Effect of Day-Level Congruence Between Felt Responsibility for Change and Willingness to Take Risks
Authors: Park In-Jo , Choi Jin Nam , Myeong Hwayeon , Hai Shenyang
Published: January 2024

This study explores a potential joint effect between two proactive motives on creative performance. Departing from the assumption of motivation as a relatively stable between-person construct, we also pay attention to the within-person process to examine how daily fluctuations of proactive motives affect daily idea generation, leading to creative performance. Specifically, drawing on job demands–resources theory, we theorize a joint effect of two proactive motives at the within-person level: daily felt responsibility for change (DFRC) and daily willingness to take risks (DWTR). We test our hypotheses by analyzing data collected from 135 employees and their supervisors by using the experience sampling method followed by multiwave field surveys. Daily idea generation is high when the DFRC and DWTR have high congruence, particularly when both motives are high rather than low. In addition, daily idea generation mediates the effect of the DFRC and DWTR congruence on employee creative performance as appraised by supervisors. Moreover, seeking feedback from coworkers strengthens the indirect effect of the DFRC and DWTR congruence on employee creative performance via daily idea generation. This study offers a fine-grained view of motivational mechanisms and employee social behavior that lead to creative performance in the workplace.
Generalized derivatives of optimal-value functions with parameterized convex programs embedded
Authors: Song Yingkai , Barton Paul I.
Published: January 2024

This article proposes new practical methods for furnishing generalized derivative information of optimal-value functions with embedded parameterized convex programs, with potential applications in nonsmooth equation-solving and optimization. We consider three cases of parameterized convex programs: (1) partial convexity—functions in the convex programs are convex with respect to decision variables for fixed values of parameters, (2) joint convexity—the functions are convex with respect to both decision variables and parameters, and (3) linear programs where the parameters appear in the objective function. These new methods calculate an LD-derivative, which is a recently established useful generalized derivative concept, by constructing and solving a sequence of auxiliary linear programs. In the general partial convexity case, our new method requires that the strong Slater conditions are satisfied for the embedded convex program’s decision space, and requires that the convex program has a unique optimal solution. It is shown that these conditions are essentially less stringent than the regularity conditions required by certain established methods, and our new method is at the same time computationally preferable over these methods. In the joint convexity case, the uniqueness requirement of an optimal solution is further relaxed, and to our knowledge, there is no established method for computing generalized derivatives prior to this work. In the linear program case, both the Slater conditions and the uniqueness of an optimal solution are not required by our new method.