bluuebunny/crossref_metadata_2025 huggingface dataset:
Varicella-zoster virus meningitis with hypoglycorrhachia, presenting with painless occipital herpes zoster mimicking atopic dermatitis
Authors: Inamoto Aya , Taniguchi Tomohiro , Fujii Yasumitsu , Miyoshi Sonoko
Published: January 2025

Varicella-zoster virus (VZV) is a known cause of meningoencephalitis, typically in immunocompromised inpatients. We report a case of meningitis caused by VZV in an immunocompetent man in his 20s. Diagnosis was delayed due to the atypical presentation of painless occipital zoster mimicking atopic dermatitis, and the presence of hypoglycorrhachia in his cerebrospinal fluid. The clinical diagnosis of VZV meningitis poses significant diagnostic challenges, and nucleic acid tests for VZV detection are recommended for patients with severe cases who require empiric acyclovir treatment.
Bilateral hippocampal toxicity in a patient using kratom
Authors: Rao Abhinav K , Lee Thomas J , Bodle Jeffrey
Published: January 2025

As an emerging toxic recreational drug, kratom use has been associated with a range of adverse effects, but reports of structural changes in the central nervous system are rare. We report a case of a young man in his 20s with a history of anxiety and depression who presented with an altered mental status and anterograde and retrograde amnesia following kratom use. His labs showed elevated alanine aminotransferase and ammonia levels, and his MRI revealed bilateral hippocampal T2 hyperintensity signal changes. Following cessation of kratom and supportive care, the patient improved. This case highlights the importance of considering kratom as a potential cause of neurological symptoms in patients presenting with an altered mental status due to toxic ingestion.
Polymicrobial empyema in a patient with lung adenocarcinomacontainingCapnocytophaga sputigena
Authors: Joshi Tejas , Albaba Isam
Published: January 2025

A man in his 60s with advanced COPD and lung adenocarcinoma presented with sepsis and acute hypoxaemic respiratory failure. Imaging revealed bilateral pleural effusions, and he was found to have a polymicrobial empyema which includedCapnocytophaga sputigena. Despite appropriate treatment, he continued to deteriorate and ultimately died of sepsis.Capnocytophagaspecies, typically benign constituents of the oral microbiota, rarely can instigate pleuropulmonary infections, especially in immunocompromised individuals. We highlight the difficulty in the identification and the optimal antimicrobial treatment ofCapnocytophagain the setting of growing antibiotic resistance.
Clear cell variant of calcifying epithelial odontogenic tumour (Pindborg tumour) of the mandible
Authors: Chellapandian Naveenaa , Baliah John , Santhanam Vidyalakshmi , Mukherjee Aditi
Published: January 2025

A calcifying epithelial odontogenic tumour (CEOT) is a rare benign odontogenic tumour of epithelial origin accounting for approximately 1% of all odontogenic tumours. The intraosseous form occurs more commonly in the posterior mandible whereas the extraosseous form is common in the anterior maxilla. CEOT is often asymptomatic and presents with a painless swelling of the mandible. Various histopathological variants of CEOT have been reported in the literature such as clear cell, Langerhans cell and CEOT with cementum-like areas with a 10–20% local recurrence. We report a case of a clear cell variant of CEOT in the left posterior mandible associated with an impacted third molar exhibiting its characteristic driven snow radiographic appearance. In addition, a few areas showed soap bubble multilocular presentation, change in trabeculae pattern and pathological fracture with the cupping type of root resorption in the mandibular second molar. Histopathologically, Liesegang rings were seen in the epithelium.
Retinal graft dislocation managed by repeat autologous retinal transplant for refractory macular hole
Authors: Hansraj Saarang , Narayanan Raja
Published: January 2025

A septuagenarian man presented with a visual acuity of hand motions and a large refractory macular hole (MH). We performed an autologous retinal transplant (ART) and covered the graft with fibrin glue without any endotamponade. The autograft was found to have dislocated from the MH when the patient was reviewed 1 week later. He was admitted for repeat ART surgery, where 1000 centistoke silicone oil was injected instead of fibrin glue and advised the patient to maintain a face-down position for 1 week. 1 month after the second surgery, the patient had a visual acuity of 20/200, N18. The graft was integrated at the MH site, with both donor sites well lasered and the retina attached.

Our case suggests that a short-acting bioadhesive such as fibrin glue may not provide sufficient duration of support until adequate retino-retinal adhesion forms between the host and retinal graft.
Myofibroblastoma of the breast mimicking carcinoma: a diagnostic challenge with a crucial role for histopathology and immunohistochemistry
Authors: Nerune Savitri M , Sasnur Prasad , Das Sayandeep K , Jacob Kezia Anna
Published: January 2025

Myofibroblastoma is a rare mesenchymal tumour known for its benign nature but complex diagnostic pathway. A woman in her 40s presented with a painless breast mass, initially reported as a fibroadenoma on ultrasound mammography and as a benign to borderline phyllodes tumour on fine needle aspiration cytology. Contrast-enhanced CT was reported as carcinoma of the breast with Breast Imaging and Reporting Data System (BIRADS)-6. Based on these findings, a modified right radical mastectomy was performed. This case highlights the limitations of radiological modalities in diagnosing myofibroblastoma due to its diverse morphological spectrum. The definitive diagnosis was established through extensive histopathological examination and immunohistochemistry, which demonstrated the tumour’s unique immunoprofile, showing strong positivity for CD34 and focal positivity for desmin and Bcl-2. This case underscores the role of histopathology and immunohistochemistry in distinguishing myofibroblastoma from other breast lesions, emphasising the need for high diagnostic accuracy and thorough evaluation to guide appropriate management and avoid unnecessary, aggressive treatments.
Strengthening advanced therapy for sickle cell disease in Africa: experience from sickle cell disease centre in Dar es Salaam, Tanzania
Authors: Bukini Daima , Rifai Aisha , Kanza Collin , Luoga Fredrick , Maingu Deogratius , Kassim Kassim , Mashaka Jennifer , Kisali Eka Patricia , Karim Salmaan , Alimohamed Mohamed Zahir , Manongi Janeth , Lema Winfrida , Chuwa Harrison , Konteh Sisawo , Urio Florence , Minja Irene Kida , Balandya Emmanuel , Moshi Grace , Makani Julie
Published: January 2025

Despite progress in healthcare services for individuals living with sickle cell disease (SCD) in Africa, substantial gaps remain in advanced treatments for SCD. To help address this burden, Tanzania has established one of the largest single-centre SCD programmes in the world and developed an advanced therapy programme for SCD focused on patient engagement and advocacy, clinical activities involving exchange blood transfusion (ExBT) and haematopoietic stem cell transplant (HSCT), gene therapy (GT) preparedness, and enabling partnerships. This report describes the programme’s genesis, structure and progress achieved. Patient engagement camps and patient-focused workshops conducted since early 2021 have involved more than 150 patients, family caregivers and healthcare providers. A patient registry was established by screening 1500 patients eligible for advanced therapies with 157 identified to benefit from advanced treatments for SCD. Out of which 22 patients received ExBT, and human leucocyte antigen typing was conducted on 127 individuals to establish a registry of family members with potential to be HSCT donors. Target product profiles were devised for minimum and optimum criteria of GT products to guide drug discovery and development efforts, and qualitative research was conducted to investigate factors anticipated to influence successful adoption of GTs for SCD in Africa. The programme’s multifaceted components have been enabled by institutional networks and collaborations established at national, regional and global levels. The programme presented opportunities to deliver cost-effective advanced treatment and curative options for SCD in Tanzania and lessons learnt may be applicable to inform similar efforts in other African regions where SCD is highly endemic.
Efficacy and safety of an algorithm using C-reactive protein to guide antibiotic therapy applied through a digital clinical decision support system: a study protocol for a randomised controlled clinical trial
Authors: Rezende Vitoria Moura Leite Rabelo , Borges Isabela Nascimento , Ravetti Cecilia Gomez , De Souza Renan Pedra , Vassalo Paula Frizera , Caldas Ana Clara de Paula , Gatto Felipe Rodrigues , Okamura Getulio Hideyoshi , Lacerda Raquel Lopes de Brito , Povoa Pedro R , Nobre Vandack
Published: January 2025

Introduction

The escalating resistance of microorganisms to antimicrobials poses a significant public health threat. Strategies that use biomarkers to guide antimicrobial therapy—most notably Procalcitonin (PCT) and C-reactive protein (CRP)—show promise in safely reducing patient antibiotic exposure. While CRP is less studied, it offers advantages such as lower cost and broader availability compared with PCT.

Methods and analysis

This randomised clinical trial aims to evaluate a novel algorithm for non-critically ill adult patients. The algorithm incorporates key clinical variables and CRP behaviour. It will be applied through a mobile application as a digital clinical decision support system. The primary goal will be to assess the algorithm’s effectiveness in reducing treatment duration compared with standard care based on current guidelines, while ensuring patient safety by monitoring the occurrence of adverse events.

Ethics and dissemination

Only patients who agree to participate in the study after reading the informed consent form will be included. This project was submitted for consideration to the Research Ethics Committee of the Federal University of Minas Gerais (COEP-UFMG) and received approval (Approval Number: 5.905.290). Collection of clinical and laboratory data from 200 patients is expected, extracted from electronic medical records and laboratory systems, along with serum samples stored for potential future analyses. Data will be preserved using the Research Electronic Data Capture platform, and serum samples will be stored in a regulated biorepository at UFMG. Access will be controlled via credentials, with privacy protections and anonymisation prior to sharing, which will occur during scientific publications.

Trial registration number

This trial was registered on ClinicalTrials.gov (NCT05841875) and was last updated on 5 December 2024 at 12:49.
Avoiding never events in orthopaedics theatres: a quality improvement project
Authors: Bhavanasi Bhaskar Amarnath , Kulkarni Shrikant
Published: January 2025

Never events in the operating room are a surgeon’s nightmare, with an incidence rate of 54%. These events are highly stressful for theatre staff and significantly compromise patient safety. The aim of this project is to avoid never events in trauma and orthopaedic theatres by ensuring that theatre staff adhere to the surgical pause and imaging pause protocols through regular audits.

This prospective study was conducted in both trauma and elective orthopaedic theatres. It involved theatre staff members who were not part of the surgical team. The study was designed to take place on random days across different theatres, with the operating team unaware of the audit to ensure genuine behaviour and compliance.

The audits focused on observing whether the surgical and imaging pause protocols were followed correctly. These protocols are critical for verifying patient identity, the surgical site, and the specific procedure and confirming the correct imaging is available and reviewed before proceeding. Data collected and corrective actions were implemented when non-compliance was observed, and data on compliance rates were systematically collected and analysed.

Preliminary results indicate a substantial increase in compliance with both the surgical and imaging pause protocols, corresponding with a reduction in the occurrence of never events. Theatre staff reported improved understanding and confidence in performing these safety checks The use of external auditors who were not part of the surgical team provided an unbiased assessment of compliance, enhancing the reliability of the findings.

In conclusion, the project demonstrates that regular audits, and data collected by non-surgical team staff, significantly improve adherence to surgical and imaging pause protocols, thereby reducing the incidence of never events in trauma and orthopaedic theatres. This approach highlights the importance of continuous monitoring and education in fostering a culture of safety and precision in surgical practice.
Plasma membrane-coated nanoparticles and membrane vesicles to orchestrate multimodal antitumor immunity
Authors: Ito Yusuke , Kasuya Hitomi , Kataoka Mirei , Nakamura Noriko , Yoshikawa Toshiaki , Nakashima Takahiro , Zhang Haosong , Li Yang , Matsukawa Tetsuya , Inoue Satoshi , Oneyama Chitose , Ohta Seiichi , Kagoya Yuki
Published: January 2025

Background

A number of immunotherapeutic approaches have been developed and are entering the clinic. Bispecific antibodies (BsAbs) are one of these modalities and induce robust efficacy by endogenous T cells in several hematological malignancies. However, most of the treated patients experience only a temporary benefit. Currently available BsAbs provide only anti-CD3 antibody-mediated T-cell stimulation, but not the costimulation or cytokine signaling essential for full T-cell activation. Here, we hypothesized that the simultaneous input of more comprehensive signals would elicit more robust and durable effector T-cell functions.

Methods

We genetically engineered the leukemia cell line K562 to express BsAbs, costimulatory ligands, cytokines, and blocking antibodies against immune checkpoint molecules on the cell surface, from which we obtained plasma membrane fractions by mechanical homogenization and subsequent isolation steps. Plasma membranes were reconstituted on the poly (lactic-co-glycolic acid) surface to generate membrane-coated nanoparticles (NPs). Alternatively, nano-sized membrane vesicles (MVs) were generated by ultrasonic dispersion of the isolated membranes. The antitumor function of NPs and MVs loaded with various immunomodulatory factors was evaluated in vitro and in vivo.

Results

Both membrane-coated NPs and MVs induced BsAb-mediated antigen-specific cytotoxic activity in non-specific T cells, with MVs inducing a slightly better response in vivo. Importantly, T-cell activation was elicited only in the presence of target tumor cells, providing a safety advantage for clinical use. NPs and MVs expressing costimulatory molecules (CD80/4-1BBL) and cytokines (interleukin (IL)-7/IL-15) further enhanced effector T-cell function and induced therapeutic efficacy in vivo. In addition, MVs expressing immune checkpoint antibodies and inflammatory cytokines IL-12 and IL-18 induced objective antitumor responses in solid tumor models partly by converting immunosuppressive macrophages to proinflammatory phenotypes and inducing cytotoxic T-cell infiltration into the tumor. Finally, we showed that MVs were also engineered to activate natural killer (NK) cells by loading multiple ligands. MVs loaded with BsAbs, 4-1BBL, IL-15, and IL-21 induced NK-cell cytotoxic activity in an antigen-specific manner.

Conclusions

We developed antitumor NPs and MVs that efficiently induced antitumor immune responses in vivo by simultaneously delivering multiple immunostimulatory signals to endogenous T cells. This platform enables the delivery of desired combinations of antitumor immune signals into T cells and NK cells.
Transient lymphocyte count decrease correlates with oncolytic adenovirus efficacy in humans: mechanistic and biomarker findings from TUNIMO phase I trial
Authors: Pakola Santeri A , Clubb James H A , Kudling Tatiana V , van der Heijden Mirte , Jirovec Elise , Arias Victor , Haybout Lyna , Peltola Katriina , Alanko Tuomo , Sormunen Jorma , Pellinen Teijo , Taipale Kristian , Quixabeira Dafne C A , Kistler Claudia , Havunen Riikka , Sorsa Suvi , Santos Joao M , Cervera-Carrascon Victor , Hemminki Akseli
Published: January 2025

Background

Oncolytic viruses (OVs) are promising immunotherapeutics to treat immunologically cold tumors. However, research on the mechanism of action of OVs in humans and clinically relevant biomarkers is still sparse. To induce strong T-cell responses against solid tumors, TILT-123 (Ad5/3-E2F-d24-hTNFa-IRES-hIL2, igrelimogene litadenorepvec) was developed. TILT-123 encodes two transgenes: tumor necrosis alpha (TNFa) and interleukin-2 (IL-2). TUNIMO (NCT04695327) was a phase I clinical trial using TILT-123 in patients with advanced solid tumors aiming to assess the safety, efficacy, and immunological effects of TILT-123. Research presented in this study evaluated the immunological effects of TILT-123 in the TUNIMO trial by using biological samples collected from the patients during the study, with an objective to leverage the findings to develop possible biomarkers of response and gain insights into possible synergistic combination treatments.

Methods

20 patients with advanced solid tumors were treated with TILT-123. Response to therapy was assessed with contrast-enhanced CT and fluorodeoxyglucose positron emission tomography, along with overall survival (OS) calculation. Biological samples from patients were collected in the form of blood and tumor biopsies. Collected samples were analyzed with immunohistochemistry, transcriptomics, proteomics, and flow cytometry.

Results

TILT-123 induced cyclical decreases in blood lymphocyte count, and more substantial blood lymphocyte count correlated with better radiographical response and longer OS. Lymphocyte count findings were confirmed with external control dataset of 96 patients. More substantial lymphocyte count change was linked to stronger immune activation in plasma proteome after intravenous TILT-123 and the presence of TILT-123 mRNA in tumors. Regarding other assays. tumor biopsies profiled showed increased amounts of CD8+ T cells, CD4+ T cells and NK cells after intravenous TILT-123, but not after intratumoral TILT-123. Transcriptional differences were seen in tumors after intravenous therapy and intratumoral therapy, with patients benefitting therapy showing stronger downregulation of immune activation at all time points.

Conclusions

TILT-123 therapy induced accumulation of effector lymphocytes in tumors. Peripheral lymphocyte count decrease is a promising biomarker for assessing oncolytic adenovirus therapy response.
Addressing residual and recurrent aneurysms post-Woven EndoBridge device embolization: a systematic review and meta-analysis
Authors: Jaikumar Vinay , Lim Jaims , Moser Matthew D , Okai Bernard , Francois Hendrick , Cadar Ana E , Waqas Muhammad , Monteiro Andre , Lai Pui Man Rosalind , Davies Jason M , Snyder Kenneth V , Levy Elad I , Siddiqui Adnan H
Published: January 2025

Background

Early literature on the Woven EndoBridge (WEB) device reported 80–90% adequate aneurysm occlusion but low complete occlusion (40–55%). It is uncertain whether residual or recurrent aneurysms require re-treatment to prevent future rupture.

Objective

To systematically review the literature to meta-analyze occlusion and complication rates after re-treatment of these aneurysms.

Methods

PubMed and EMBASE were queried for ‘re-treatment’ of ‘recurrent’ or ‘residual’ aneurysms treated with the WEB device. Studies reporting strategies and outcomes were included. Patient and aneurysm characteristics, outcomes, and complications were extracted. Meta-analyses were conducted on variables reported by three or more studies.

Results

We included 15 studies of 220 patients (220 aneurysms) with a mean age of 57.8 years (95% CI 55.1 to 60.7 years). At baseline, 42.8% (95% CI 35% to 51%) of aneurysms were ruptured, had a mean 8.6 mm dome (95% CI 7.3 to 10 mm) and a mean 5.2 mm neck (95% CI 4.7 to 5.7 mm), and 69.85% were at bifurcations (95% CI 47.63% to 85.51%). At mean 11.2 months' follow-up (95% CI 8 to 15.6 months), 75.9% (95% CI 66.1% to 83.5%) had residual dome filling, predominantly from incomplete occlusion in 84.7% of cases (95% CI 66.6% to 93.9%). Endovascular management was used in 82.5% (95% CI 72.6% to 89.3%) of recurrences, with stent-assisted or flow diverter-assisted coil embolization being used in 42.4% (95% CI 32.7% to 52.8%). Overall, complication rates were 8.9% (95% CI 4.9% to 15.6%) thromboembolic and 8% (95% CI 4.3% to 14.2%) device-related. Complete angiographic occlusion after re-treatment was achieved in 64.1% (95% CI 52.6% to 74.2%), of patients, with 15.2% (95% CI 8.8% to 24.9%) requiring additional re-treatment.

Conclusion

Our review reports excellent safety and modest occlusion outcomes with re-treatment of recurrent or residual aneurysms post-WEB embolization. Outcomes with observational management of residual or recurrent aneurysms are lacking, questioning the requirement for re-treatment. Endovascular strategies demonstrated excellent safety and additional re-treatment rates, highlighting their expanding role in post-WEB recurrences.
Workflow improvements from automated large vessel occlusion detection algorithms are dependent on care team engagement
Authors: Ebirim Emmanuel C , Le Ngoc Mai , Samaha Joseph N , Azeem Hussain , Iyyangar Ananya , Ballekere Anjan N , Dhanjani Saagar , Giancardo Luca , Lee Eunyoung , Sheth Sunil A
Published: January 2025

Background

Automated machine learning (ML)‐based large vessel occlusion (LVO) detection algorithms have been shown to improve in‐hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction are required for these benefits remains incompletely characterized.

Methods

This analysis was conducted as a pre‐planned post-hoc analysis of a randomized prospective clinical trial. ML‐based LVO detection software was implemented at four comprehensive stroke centers (CSCs) from January 1, 2021, to February 27, 2022. Patients were included if they underwent endovascular thrombectomy for LVO acute ischemic stroke. ML software utilization was quantified as the total number of active users and the ratio of the number of comments to the number of patients analyzed by the software by site per week. Primary outcome was the reduction in DTG relative to pre‐ML implementation by hospital utilization level. Data are expressed as median (IQR).

Results

Among 101 patients who met the inclusion criteria, the median age was 71 years (IQR 59–79), with 48.5% being female. CSC 4 had the greatest number of total active users per week (32.5 (27.5–34.5)), and comment-to-patient ratio per week (5.8 (4.6–6.9)). Increased ML software utilization was associated with improvements in DTG reduction. For every 1 unit increase in the comment-to-patient ratio, DTG time decreased by 2.6 (95% CI −5.09 to –0.13) min, while accounting for site-level random effects. Number of users-to-patient was not associated with a reduction in DTG time (β=−0.22, 95% CI −1.78 to 1.33).

Conclusions

In this post-hoc analysis, user engagement with software, rather than total number of users, was associated with site-specific improvements in DTG time.
Dark coloured scalars impact on single and di-Higgs production at the LHC
Authors: Gabriel Pedro , Mühlleitner Margarete , Neacsu Daniel , Santos Rui
Published: January 2025

The search for Dark Matter (DM) at colliders is primarily pursued via the detection of missing energy in particular final states. These searches are based on the production and decay processes where final states include DM particles and at least one Standard Model (SM) particle. DM will then reveal itself as missing energy. An alternative form to get a hint of a dark sector is via loop contribution to SM processes. In this case, it is not even relevant if the new particles have their origin in the dark sector of the model. In this work we discuss the impact of an arbitrary number of coloured scalars with

$$Z_2$$

Z
2

-odd parity in single Higgs and double Higgs production at the Large Hadron Collider (LHC), and we show their complementarity. We determine the range of variation of the corrections relative to the SM for an arbitrary number of coloured scalars n. We discuss the cases

$$n=1$$

n
=
1

and

$$n=2$$

n
=
2

for a specific model in more detail, which includes direct searches at the LHC. We also find that the electroweak observable T parameter imposes significant restrictions on the difference of the heavy coloured scalar masses.
Generation of Personalized Urban Public Space Color Design Scheme Assisted by Artificial Intelligence
Authors: Cheng XiaoTing , Wang Ming , Fan XingQi
Published: January 2025

This research focuses on the generation of urban public space color design schemes using Artificial Intelligence (AI). The designed AI-based system predicts colors for the environment, culture, and users and designs a color palette for smart cities. Neural networks and clustering algorithms are used to determine the best hues and shades, depending on the input parameters like climate, architectural style, and general looks in a specific region. It evokes sophisticated colors in varied urban contexts, URBAN FABRICS proposes a specific color answer to the aesthetic and performative beautification of the public realm. In addition to adopting elements of AI binding into the design principles, the system enables dynamic colors to adapt to the changing needs and external conditions. Testing the model in multiple cities demonstrated its ability to generate unique, context-sensitive designs, improving both aesthetic value and user satisfaction. This research highlights the role of AI in modern urban planning, presenting an innovative approach to color design that balances artistic creativity with data-driven insights. The findings offer practical implications for architects, urban planners, and designers seeking to enhance urban public spaces through personalized, AI-assisted color schemes.
Research on Evaluation of Hotel Digitization Effect Assisted by Extreme Learning Machine in Artificial Intelligence Environment
Authors: Shi Hongshuai , Zhong Zhixian
Published: January 2025

Hotels streamline operations, provide more personalized service, streamline communication, automate procedures, and gather feedback for ongoing development using modern digital technologies like customer care chatbots, mobile guest applications, and property management systems. Batch, sequential, and incremental learning all make heavy use of the Extreme Learning Machine (ELM) because of its efficient and rapid learning rate, rapid convergence, strong generalizability, and simplicity of implementation. By automating repetitive tasks, Artificial Intelligence (AI) improves the hospitality sector’s efficiency and quality on service it provides to customers and employees. Using AI-driven automated systems, hotels may improve inventory management, track and manage energy use, and simplify cleaning schedules. The challenging characteristics of smart flood detection and alert systems are that they lack expertise, streamline operations and provide personalized guest services. Hence, in the proposed method, the Artificial Intelligence Environment enabled Wireless Sensor Network (AIE-WSN), which integrates a hotel digitization effect in an ELM. In addition, case studies and expert interviews provide practical insights into how hotels have used and benefited from financial management systems driven by AI. The research shows that hotels may greatly benefit from AI tools, including personalized pricing strategies, spending monitoring systems, fraud detection algorithms, and predictive analytics when making financial decisions through WSN. The hotel industry is undergoing digitalization, adopting AI-WSN solutions to track products’ provenance and monitor their history, among the many benefits of the proposed approach. It can help with supply chain management and adopting more efficient practices.
Emerging Trends on Hybrid Artificial Intelligence Framework for Transforming Heavy Machinery with Robots and Energy Efficiency
Authors: Liu Yanping , Song Li , Yang Chunxia
Published: January 2025

Today, heavy machinery can be equipped with robots operated by artificial intelligence (AI) to streamline operations, decrease human labor, and increase efficiency. Intelligent technologies like these can boost productivity by carrying out routine tasks with extreme accuracy. Since robots reduce risks to human workers, robots with AI algorithms and sensors could be used in hazardous environments. In certain contexts, including building site management, mining, or handling hazardous materials, safety must take precedence above everything else. Analytics from this study, aided by AI, have opened the door to predictive maintenance procedures. To detect equipment problems, the Hybrid Artificial Intelligence Framework (HAIF) examines sensor data in conjunction with historical patterns. The objective is to avoid expensive failures and downtime. Optimization of equipment utilization, energy consumption, and fuel consumption can be achieved by applying AI-driven machine learning algorithms. Several advantages arise from energy waste, including cost avoidance and enhanced operational efficacy. Robots can do exact alignments, measurements, and operations with the help of AI vision technologies. This precision significantly impacts the manufacturing, agricultural, and construction industries. Artificial intelligence has the potential to optimize the allocation of resources, the use of heavy equipment, and supply networks by evaluating massive amounts of data.
A Comprehensive Survey of Benchmarks for Improvement of Software's Non-Functional Properties
Authors: Blot Aymeric , Petke Justyna
Published: January 2025

Despite recent increase in research on improvement of non-functional properties of software, such as energy usage or program size, there is a lack of standard benchmarks for such work. This absence hinders progress in the field, and raises questions about the representativeness of current benchmarks of real-world software.

To address these issues and facilitate further research on improvement of non-functional properties of software, we conducted a comprehensive survey on the benchmarks used in the field thus far. We searched five major online repositories of research work, collecting 5,499 publications (4,066 unique), and systematically identified relevant papers to construct a rich and diverse corpus of 425 relevant studies.

We find that execution time is the most frequently improved property in research work (63%), while multi-objective improvement is rarely considered (7%). Static approaches for improvement of non-functional software properties are prevalent (51%), with exploratory approaches (18% evolutionary and 15% non-evolutionary) increasingly popular in the last 10 years. Only 39% of the 425 papers describe work that uses benchmark suites, rather than single software, of those SPEC is most popular (63 papers). We also provide recommendations for future work, noting, for instance, lack of benchmarks for non-functional improvement that covers Python, JavaScript, or mobile devices. All the details regarding the 425 identified papers are available on our dedicated webpage:
https://bloa.github.io/nfunc_survey
.
Multi-Tenant Cloud FPGA: A Survey on Security, Trust and Privacy
Authors: Kawser Ahmed Muhammed , Panoff Kealoha Maximillian , Mandebi Mbongue Joel , Saha Sujan Kumar , Nghonda Tchinda Erman , Mbua Peter Esenju , Bobda Christophe
Published: January 2025

With the growing demand for enhanced performance and scalability in cloud applications and systems, data center architectures are evolving to incorporate heterogeneous computing fabrics that leverage CPUs, GPUs, and FPGAs. Unlike traditional processing platforms like CPUs and GPUs, FPGAs offer the unique ability for hardware reconfiguration at run-time, enabling improved and tailored performance, flexibility, and acceleration. FPGAs excel at executing large-scale search optimization, acceleration, and signal processing tasks while consuming low power and minimizing latency. Major public cloud providers, such as Amazon, Huawei, Microsoft, Alibaba, and others, have already begun integrating FPGA-based cloud acceleration services into their offerings. Although FPGAs in cloud applications facilitate customized hardware acceleration, they also introduce new security challenges that demand attention. Granting cloud users the capability to reconfigure hardware designs after deployment may create potential vulnerabilities for malicious users, thereby jeopardizing entire cloud platforms. In particular, multi-tenant FPGA services, where a single FPGA is divided spatially among multiple users, are highly vulnerable to such attacks. This paper examines the security concerns associated with multi-tenant cloud FPGAs, provides a comprehensive overview of the related security, privacy and trust issues, and discusses forthcoming challenges in this evolving field of study.
An Extended Study of the Performance of Flexible Controllers Composed of Micro-controllers
Authors: Siqueira Bento , Ferrari Fabiano , de Lemos Rogerio
Published: January 2025

Generic controllers for self-adaptive systems can be configured parametrically according to system needs, even though their reuse is restricted because of the wide range of services that may be provided by each stage of a feedback control loop, like MAPE-K. Rainbow is a typical example of such a generic, monolithic controller. This article revisits and extends prior work that advocates structurally flexible controllers, as ensembles of micro-controllers each providing specific services. We experimented with our approach with three different architectural configurations for the controller: monolithic, decentralised, and decentralised with a meta-controller. Our results indicate that despite the decentralised configuration with a meta-controller demanding more computational resources, it performed comparatively well compared to the other configurations, including when measuring the target system’s response time. Moreover, we found that variations of the control loop timing at the different layers of the controller impact the stability of the target system. We have also evolved the controller by adding a new micro-controller, which caused no impact on the other micro-controllers, and mostly kept the target system’s performance. We conclude that a multi-layered controller design, based on micro-controllers, provides the basis for defining structurally flexible controllers at operational-time, and may promote reuse at development-time.
Ownership Verification for Federated Recommendation
Authors: Yang Enyue , Pan Weike , Fan Lixin , Gu Hanlin , Li Zhitao , Yang Qiang , Ming Zhong
Published: January 2025

Most federated learning-based recommender systems allow clients to access a well-trained high-quality model locally, which provides adversaries with the opportunity to infringe the legitimate copyright of the model. In response, we study an emerging and important problem, i.e., copyright protection of a federated recommendation model, which has not yet been addressed in the community of federated learning or recommender systems. We propose the first backdoor-based ownership verification scheme for federated recommendation called OVFR, which enables the server to claim its ownership for a given suspicious recommendation model. Firstly, we propose to generate a trigger set tailored to recommendation scenarios. In particular, we generate some fake users and items, and then construct a set of fake users with fake interaction records as a trigger set. Moreover, we ensure that the distribution of the popularity of the fake items follows a long-tailed distribution for the effectiveness of the incorporated watermarking. To provide robustness assurance, we propose two different hybrid strategies to make the embeddings of the fake items similar to those of the real items. Secondly, we focus on effectively learning from a trigger set for recommendation scenarios. In particular, we design a mean square error (MSE) loss function and a contrastive loss function for incorporating the backdoor-based watermarking into the item embeddings, since the item embeddings are often more valuable and easier to be accessed than other parameters of a federated recommendation model. We then design a contrastive loss function to reduce the risk of the fake items being detected. Extensive experiments on three public datasets show the effectiveness of our OVFR in terms of ownership verification, model performance, and robustness.
Mitigation of Pitting on Nitrogen-Doped Niobium Surfaces through Two-Step Electropolishing
Authors: Chouhan V. , Ring T. , Wu G. , Viklund E.
Published: January 2025

Surface processing of niobium superconducting RF cavities used in particle accelerators is crucial for determining their performance. The nitrogen (N)-doping method, developed at Fermilab, enhances the cavities’ quality factor by doping the cavity’s interior surface with N atoms at 800 °C. After N-doping, electropolishing (EP) is employed to remove the niobium nitride phases and attain the desired concentration of interstitial N atoms. This study explores the effects of EP conditions on N-doped niobium samples. The samples were electropolished at 5 to 40 °C and voltages between 3 and 22 V. Different EP voltage ranges produced two types of pits, classified based on their sizes. Larger pits, linked to higher voltages, are also affected by the reaction rate. Pitting could be reduced at a lower temperature and adequate EP voltage. However, to effectively minimize gas evolution forming large-sized pitting, peeling off the top nitride layer before EP might be beneficial. This was achieved through precise low-voltage etching, forming a two-step EP process. The process involves removing the top 100–200 nm layer at a low voltage, followed by standard EP to remove the required material. This two-step EP process effectively mitigated the pitting risk associated with gas evolution on N-doped surfaces.
Sex differences in the metabolism of glucose and fatty acids by adipose tissue and skeletal muscle in humans
Authors: Costa Damla N. , Santosa Sylvia , Jensen Michael D.
Published: January 2025

Adult males and females have markedly different body composition, energy expenditure, and have different degrees of risk for metabolic diseases. A major aspect of metabolic regulation involves the appropriate storage and disposal of glucose and fatty acids. The use of sophisticated calorimetry, tracer, and imaging techniques have provided insight into the complex metabolism of these substrates showing that the regulation of these processes varies tremendously throughout the day, from the overnight fasting condition to meal ingestion, to the effects of physical activity. The sexual dimorphism in substrate metabolism is most readily observed in how fatty acids are stored and mobilized. The objective of this review is to provide a comprehensive and critical summary of the reported sex-differences in the mobilization, oxidation and storage of fat and carbohydrate in adipose tissue and skeletal muscle. We will describe how adipose tissue lipolysis differs between sexes, and how this varies between fed, fasted and exercise conditions. We will also review what is known about endogenous and exogenous fatty acid storage in adipose tissue and muscle, as well as how oxidation compares between men and women in response to exercise. What has been learned about the cellular level regulation of these processes will be described. Although glucose metabolism exhibits fewer differences between men and women, we will also review the existing knowledge on this topic.
Design and Experimental Study of Composite Cross Arm Tension Release Device
Authors: Li Wenbin , Lin Junzhe , Wang Xinlong , Li Yanlin , Zhang Xiaolei , Bai Junfeng , Wang Dehong
Published: January 2025

The composite cross arm tower exhibits excellent electrical performance, which contributes to a reduction in the width of transmission line corridors, minimizes the use of steel in transmission towers, and mitigates issues such as wind bias tripping. This functionality supports the low‐carbon design of overhead transmission lines, emphasizing the importance of quality and efficiency. However, the elimination of the suspension insulator string in composite cross arm linear towers leads to significant longitudinal unbalanced tension during adverse conditions such as conductor line breaks or ice accumulation. This excessive force can cause local damage or even collapse of the tower due to overstressing of the diagonal members. To address this challenge, we propose a new composite cross arm structure incorporating a C‐shaped rotating device designed to alleviate unbalanced tension in composite cross arm towers. The mechanical performance of this structure was assessed through both full‐scale tests and finite element simulations, confirming that the structure operates within an elastic range. The rotation axis was identified as the weakest point, with stress peaks remaining significantly below the yield strength, thereby indicating a high level of safety and a considerable safety margin. The C‐shaped rotating device features a 380 mm range of motion and effectively releases unbalanced tension during actual line operations. Overall, the new composite cross arm structure with the C‐shaped rotating device demonstrates favorable mechanical properties.
Artificial Intelligence–Based Psychotherapeutic Intervention on Psychological Outcomes: A Meta‐Analysis and Meta‐Regression
Authors: Lau Ying , Ang Wei How Darryl , Ang Wen Wei , Pang Patrick Cheong-Iao , Wong Sai Ho , Chan Kin Sun
Published: January 2025

Background: Artificial intelligence (AI)–based psychotherapeutic interventions may bring a new and viable approach to expanding psychiatric care. However, evidence of their effectiveness remains scarce. We evaluated the efficacy of AI‐based psychotherapeutic interventions on depressive, anxiety, and stress symptoms at postintervention and follow‐up assessments.

Methods: A three‐step comprehensive search via nine electronic databases (PubMed, Embase, CINAHL, Cochrane Library, Scopus, IEEE Xplore, Web of Science, PsycINFO, and ProQuest Dissertations and Theses) was performed.

Results: Thirty randomized controlled trials (RCTs) in 31 publications involving 6100 participants from nine countries were included. The majority (79.1%) of trials with intention‐to‐treat analysis but less than half (48.6%) of trials with perprotocol analysis were graded as low risk. Meta‐analyses showed that interventions significantly reduced depressive symptoms at the postintervention assessment (t = −4.40, p = 0.001) with medium effect size (g = −0.54, 95% CI: −0.79 to −0.29) and at 6–12 months of assessment (t = −3.14, p < 0.016) with small effect size (g = −0.23, 95% CI: −0.40 to −0.06) in comparison with comparators. Our subgroup analyses revealed that the depressed participants had a significantly larger effect size in reducing depressive symptoms than participants with stress and other conditions. At postintervention and follow‐up assessments, we discovered that AI‐based psychotherapeutic interventions did not significantly alter anxiety, stress, and the total scores of depressive, anxiety, and stress symptoms in comparison to comparators. The random‐effects univariate meta‐regression did not identify any significant covariates for depressive and anxiety symptoms at postintervention. The certainty of evidence ranged between moderate and very low.

Conclusions: AI‐based psychotherapeutic interventions can be used in addition to usual treatments for reducing depressive symptoms. Well‐designed RCTs with long‐term follow‐up data are warranted.

Trial Registration: CRD42022330228
Designing a Revenue Forecast Scheme for Analog Ensemble Method Applied Solar PV Forecasting in South Korea
Authors: del Pozo F. E. , Kim C. K. , Kim H. G. , Yun C. Y.
Published: January 2025

Power companies have found that solar irradiance forecasting is a reliable method for anticipating and preparing for the intermittent nature of renewable energy sources (RESs). However, when the percentage of RESs in the energy mix rises, there is a negative correlation between forecasting accuracy and process error, which could impact not only the grid but also the whole RES’s economic sustainability. In order to tackle this problem, this paper examines the economic implications of employing the Analog Ensemble (AnEn) forecasting model within Korea’s solar energy sector. The levelized cost of energy (LCOE) model and the revenue prediction model are applied to assess the efficacy of the AnEn. The proposed revenue scheme scheme was initiated on a 1 MW photovoltaic (PV) ground‐type power plant deployed in the mainland of South Korea. Various methods have been examined to assess the financial benefit of utilizing the AnEn, such as forecast verification and LCOE and revenue forecast scheme. Key findings reveal that the AnEn model consistently outperforms traditional models in terms of accuracy, particularly during critical solar peak months. This improved accuracy translates into more reliable predictions of solar irradiance, essential for minimizing overestimations and supporting realistic financial planning. Furthermore, the paper explores the economic incentives implemented by the Korean government to encourage precision in energy forecasting, including a structured incentive scheme tied to forecast accuracy.
Enhancing Pharmacy Warehouse Management With Faster R‐CNN for Accurate and Reliable Pharmaceutical Product Identification and Counting
Authors: Tavakoli Mohammad Javad , Fazl Fatemeh , Sedighi Mahsa , Naseri Kobra , Ghavami Mohammad , Taghipour-Gorjikolaie Mehran
Published: January 2025

The rise of digitalization and Industry 4.0 has led to significant changes in industrial warehouse management. However, managing warehouses remains challenging due to reliance on manual labor and limited automation. This article focuses on addressing issues in warehouse management, specifically in drug identification and counting. Although traditional methods such as barcode systems and RFID are common, artificial intelligence (AI) offers a promising solution. In this paper, an advanced visual recognition based on Faster R‐CNN is introduced to accurately identify and count pharmaceutical items in pharmacies. The obtained results suggest that intelligent warehouse management in pharmacies can lead to cost savings and improved efficiency. The study also compares the proposed model with popular classification methods such as CNN, SVM, KNN, YOLOv5, and SSD, showing the effectiveness of the new approach.
A Lightweight Conditional Diffusion Segmentation Network Based on Deformable Convolution for Surface Defect Detection
Authors: Chen Jiusheng , Zhao Yibo , Wang Haibing
Published: January 2025

Surface defect detection is crucial to industrial manufacturing and research for surface defects has drawn much attention. However, defects in industrial environment are very diverse. Because defects scale and poses are constantly changing and current methods lack the ability to model the deformation. To solve this problem, a lightweight conditional diffusion segmentation network based on deformable convolution is proposed. First, the conditional diffusion process is introduced for effective feature extraction; by gradually corrupting the defect images and recovering them from latent space, the model can obtain pixel‐level segmentation results in an iterative process. Second, the efficient feature extraction block is proposed to address the problem of modeling varying defects, which is designed with a partial deformable convolutional layer that can fully extract geometric features of the diverse defects to further enhance the modeling power of the proposed network. Furthermore, the hyperparameters of the diffusion process are discussed to further improve the performance of the proposed method. The experimental results on DAGM2007, MT, AeBAD, and MVTec‐AD indicate that the proposed model performs better than other baseline models.