bluuebunny/crossref_metadata_2025 huggingface dataset:
Children born to subfertile couples, how are they doing? Evidence from research
Authors: Schottler Nadine Iman , Sutcliffe Alastair G
Published: April 2024

More than 10 million children have been born with assisted reproductive technology (ART) as we begin to enter the third generation of individuals conceived by ART. Here we summarise key messages from an enlarging body of literature regarding their health. Earlier research had pointed towards increases in perinatal, neonatal and neurological risks, such as preterm birth, low birth weight, congenital malformations and cerebral palsy. Many of these risks have continued to persist in most recent work but have shown reduction. Newer research proposes long-term cardiometabolic and endocrine concerns. Fortunately, most reports conclude there is little or no risk of increased childhood malignancy or abnormal neurodevelopment. Moving forward, new research may benefit from changes in comparator groups and a better understanding of infertility per se in ART, and the confounding role it probably plays in many of the known risk associations, to reliably scan the horizon for health threats for individuals born after ART.
Denosumab and sclerotherapy for recurrent spinal aneurysmal bone cyst in a child
Authors: Singh Raj , Madasswery Sreekumar , Colman Matt , Kent Paul McKeegan
Published: April 2024

Aneurysmal bone cyst (ABC) is a non-malignant, locally destructive, blood-filled lesion in the bone that tends to grow aggressively. A young girl presented with a rapid recurrence after aggressive surgery of a large symptomatic sacral-spinal ABC. After a multidisciplinary tumour board, she was successfully treated with sclerotherapy and monthly intravenous denosumab. The patient has maintained asymptomatic for over 36 months now and has returned to full activity and strength. She never required surgery and has had radiologic resolution of the lesions. Treatment of recurrent ABC requires a multidisciplinary team approach. We believe this to be the first report to use this combined therapy to provide an alternative to morbid surgery for children with ABCs.
Scalp necrosis following preoperative endovascular embolisation of the superficial temporal artery for meningioma
Authors: Panesar Harsimran , Hatazaki Mai , Shekhtman Yevgenia
Published: April 2024

A woman in her late 50s with a left frontal lobe convexity meningioma underwent an elective endovascular embolisation of the left middle meningeal artery and distal branches of the left superficial temporal artery prior to surgical resection of the tumour. On postoperative day 46, she developed scalp necrosis, leading to poor wound healing requiring wound debridement and a complex plastic surgery reconstruction with a rotational flap. Endovascular embolisation of vascular tumours prior to surgical resection does not come without risks. The lack of consistency in the literature regarding indication, technique and outcomes makes it difficult to define the exact role of preoperative meningioma embolisation.
Management of an acute intracranial emergency in pregnancy
Authors: Brokkelkamp Petronella , Baalman Jelle H , Driesse Maarten J , Kho Kuan H
Published: April 2024

We report a case of a mid-20s primigravida at 37 weeks’ gestation who
presented with severe headache and acute neurological deterioration. The CT
brain scan showed hydrocephalus caused by a colloid cyst in the third
ventricle. The patient underwent emergency placement of an external
ventricular drain for decompression of acute hydrocephalus. Four hours
later, labour commenced spontaneously, and in view of her neurological
status, a decision was taken to perform a caesarean section under general
anaesthetics. Four days postpartum, the patient underwent an endoscopic
removal of the cyst. Intracranial emergencies during pregnancy are rare and
challenging to manage. The mortality rate can be significant. Diagnostic and
surgical intervention should not be delayed because of pregnancy. An
individualised treatment approach is required with multidisciplinary input.
The collaborative efforts of our multidisciplinary team resulted in prompt
diagnosis and surgical treatment in this case that resulted in both a
healthy mother and child.
The use of rotational thromboelastometry to guide management followingBitis nasicornisenvenoming
Authors: Nye Charles , Lalloo David Griffith , Hooper Timothy
Published: April 2024

A man in his thirties presented followingBitis nasicornisenvenoming. His coagulation was assessed using rotational thromboelastometry (ROTEM). It identified a subtle abnormality, not detected using standard laboratory assessments of coagulation, and influenced ongoing management. The abnormality resolved following treatment with antivenom. There are few documented cases of using ROTEM to assess patients following haemotoxic envenoming. This case highlights some of the potential benefits and limitations of doing so.
Chronic interstitial ectopic pregnancy presenting with a negative urine pregnancy test
Authors: Jongjakapun Apiwat , Salang Lingling , Aueaungkul Apiwat , Kleebkaow Pilaiwan
Published: April 2024

The ampulla portion of the fallopian tube is the most common site of ectopic pregnancy (70%), with approximately 2% of pregnancies implanted in the interstitial portion. In general, an interstitial ectopic pregnancy (IEP) is difficult to diagnose and is associated with a high rate of complications—most patients with an IEP present with severe abdominal pain and haemorrhagic shock due to an ectopic rupture. Chronic tubal pregnancy (CTP) is an uncommon condition with an incidence of 20%. The CTP has a longer clinical course and a negative or low level of serum beta-human chorionic gonadotropin due to perished chorionic villi. This study presents a case of a woman who was diagnosed with a chronic IEP (CIEP) which was successfully treated by surgery. This case also acts as a cautionary reminder of considering a CIEP in women of reproductive age presenting with amenorrhea, vaginal bleeding and a negative pregnancy test.
Encountering the corona mortis vessel during laparoscopic totally extraperitoneal mesh hernioplasty and its significance
Authors: Saini Vikram , Alla Sonali , Verma Himanshi , Chhabra Umesh
Published: April 2024

Corona mortis (CM) is an anastomotic vessel between the inferior epigastric or external iliac vessels and the obturator or internal iliac vessels. The Latin meaning of it is ‘crown of death’ which corresponds to massive haemorrhage caused by injury to this vessel during surgery. The incidence of this vessel is around 50% in the hemipelvis. We are presenting an intraoperative video of a right laparoscopic totally extraperitoneal mesh hernioplasty demonstrating a CM artery in the right hemipelvis. Care was taken to prevent injury to this vessel. CO2insufflation pressure was reduced to less than 10 mm Hg to see any venous variant of this vessel. Carefully, polypropylene mesh was placed without a fixation device. Anatomical knowledge of the CM vessel is therefore essential in preventing injury for surgeons who approach the inguinal and retropubic regions.
Listeriosis in pregnancy: a challenge in diagnosis
Authors: Basri Nurul Iftida
Published: April 2024

Listeriosis is a rare foodborne infection caused byListeria monocytogenes. It has been reported to be commonly found among the obstetric population, immunocompromised group and elderly, presumably due to the lower immunity status in these populations. Presentation in pregnancy is usually non-specific like fever, diarrhoea, respiratory tract symptoms and preterm rupture of membrane. These make the diagnosis challenging and may delay the correct management. We present a case of a female in her early 40s, gravida 4 para 0+3 at 27 weeks who presented with fever. She later developed preterm rupture of membrane 24 hours after admission. The leaking of liquor later changed from clear to meconium stained raising the suspicion of listeria chorioamnionitis, necessitating an emergency preterm delivery via caesarean section. The newborn acquired listeria infection and required ventilation support. He subsequently was discharged from neonatal unit after nearly 3 months of life.
National public health institutes in the Eastern Mediterranean Region: Insights from experts in the field
Authors: Abou-Taleb Hala , van Gilst Sebastian , Mohamed Nada , Mataria Awad
Published: April 2024

National public health institutes (NPHIs) are crucial to the effectiveness of public health systems, including delivering essential public health functions and generating evidence for national health policies, strategies and plans. Currently, there is a significant lack of information regarding NPHI or NPHI-like organisations in Eastern Mediterranean Region (EMR) countries, including how they fit into their broader health systems governance landscape. NPHIs exist in 12 out of 22 EMR countries, yet there is no official International Association of National Public Health Institutes (IANPHI) regional network for the EMR, despite established IANPHI networks in four other regions. In 2022, the WHO’s Eastern Mediterranean Regional Office led a study comprising an online survey and key informant interviews, which synthesised expert insights and summarised recommendations to strengthen the health systems governance-related role of NPHIs in EMR countries. Study participants included current and former high-level representatives of NPHIs, the government (eg, Ministries of Health, health regulatory authorities), multilateral organisations or non-governmental organisations focusing on health, and others identified as senior health systems governance experts from EMR. Insights and recommendations from experts varied widely, but there were also many common elements and overlaps. These included the need for enhancing NPHI functionalities and collaborative efforts with the public health sector (eg, Ministry of Health, Health Council) in health policy and decision-making formulation and implementation. This, in turn, requires advancing NPHI’s fit-for-purpose and sustainable governance and financing arrangements, improving the accessibility and transparency of health data for NPHIs, strengthening engagement and collaboration between NPHIs and other health system actors (including the private sector), and promoting a more prominent role for NPHIs in the development and implementation of public health-related policies and legislation. While many excellent insights and thoughtful strategic guidance are provided, further adaptation may be needed to implement the proposed recommendations in different EMR country contexts going forward.
The cost of inaction on health equity and its social determinants
Authors: Yerramilli Pooja , Chopra Mickey , Rasanathan Kumanan
Published: April 2024

Rising levels of inflation, debt and macrofiscal tightening are putting expenditures on the social sectors including health under immense scrutiny. Already, there are worrying signs of reductions in social sector investments. However, even before the pandemic, evidence showed the significant returns on investments in health equity and its social determinants. Emerging data and trends show that these potential returns have increased during the COVID-19 pandemic - investments in social determinants can mitigate widespread reductions in human capital and the increasing likelihood of costly syndemics, while promoting access to healthcare innovations that have thus far been inequitably distributed. Therefore, we argue that, despite immediate fiscal pressures, this is exactly the time to invest in health equity and its broader social determinants, as the returns on such investments have never been greater.
Using Mixed Reality Simulation to Improve Junior Medical Trainees’ Preparedness to Manage High-Acuity Trauma
Authors: Clarke Kirsty , Al-mukhtar Aws , Alim Lina , Nimer Amr , Hatfield Emma , Sabharwal Sanjeeve , Syed Sadie
Published: April 2024

High-acuity trauma necessitates experienced and rapid intervention to prevent patient harm. However, upskilling junior trainees through hands-on management of real trauma cases is rarely feasible without compromising patient safety. This quality education report sought to investigate whether a simulation course operated via mixed reality (MR) headset devices (Microsoft HoloLens) could enhance the clinical knowledge recall and preparedness to practice of junior trainees with no prior experience managing trauma.

The Plan–Do–Study–Act quality improvement method was used to refine six emergency trauma vignettes compatible with an MR teaching platform. Each vignette was curated by a multidisciplinary team of orthopaedic surgeons, clinical fellows and experts in simulation-based medical education. As a baseline assessment, a 2-hour emergency trauma course was delivered using traditional didactic methods to a cohort of pre-registration medical students with no clinical exposure to high-acuity trauma (n=16). Next, we delivered the MR simulation to an equivalent cohort (n=32). Clinical knowledge scores derived from written test papers were recorded for each group during and 2 weeks after each course. Each attendee’s end-of-rotation clinical supervisor appraisal grade was recorded, as determined by a consultant surgeon who supervised participants during a 2-week placement on a major trauma ward. Balancing measures included participant feedback and validated cognitive load questionnaires (National Aeronautics and Space Administration-Task Load Index).

Overall, attendees of the MR simulation course achieved and sustained higher clinical knowledge scores and were more likely to receive a positive consultant supervisor appraisal. This project serves as a proof of concept that MR wearable technologies can be used to improve clinical knowledge recall and enhance the preparedness to practice of novice learners with otherwise limited clinical exposure to high-acuity trauma.
Quality improvement collaborative approach to COVID-19 pandemic preparedness in long-term care homes: a mixed-methods implementation study
Authors: Sorensen Janice , Kadowaki Laura , Kervin Lucy , Hamilton Clayon , Berndt Annette , Dhadda Simran , Irfan Abeera , Leong Emma , Mithani Akber
Published: April 2024

Background

The devastating impact of the COVID-19 pandemic on long-term care (LTC) homes underscores the importance of effective pandemic preparedness and response. This mixed-methods, implementation science study investigated how a virtual-based quality improvement (QI) collaborative approach can improve uptake of pandemic-related promising practices and shared learning across six LTC homes in British Columbia, Canada in 2021 during the COVID-19 pandemic health emergency.

Methods

QI teams consisting of residents, family/informal caregivers, care providers and leadership in LTC homes are supported by QI facilitation and shared learning through virtual communication platforms. QI projects address gaps in outbreak preparation, prevention and response; planning for care; staffing; and family presence. Thematically analysed semi-structured qualitative interviews and a validated questionnaire on organisational readiness investigated participants’ perceptions of challenges, success factors and benefits of participating in the virtual QI collaborative approach.

Results

Nine themes were identified through interview analysis, including two related to challenges (ie, making time for QI and hands tied by external forces), four regarding factors for successes (ie, team buy-in, working together as a team, bringing together diverse perspectives and facilitators keep us on track) and three on the benefits of the QI collaborative approach (ie, seeing improvements, staff empowerment and appetite for change). Continuous QI facilitation and coaching for QI teams was feasible and sustainable virtually via video conferencing (Zoom). The QI team members showed limited engagement on the virtual communication platform (Slack), which was predominantly used by the implementation science team and QI facilitators to coordinate the study and QI projects, respectively.

Conclusions

The virtual-based QI collaborative approach to pandemic preparedness supported LTC homes to rapidly and successfully form multidisciplinary QI teams, learn about QI methods and conduct timely QI projects to implement promising practice for improved COVID-19 pandemic response.
Machine learning-based detection of sleep-disordered breathing in hypertrophic cardiomyopathy
Authors: Akita Keitaro , Kageyama Shigetaka , Suzuki Sayumi , Ohno Kazuto , Kamakura Masamitsu , Nawada Ryuzo , Takanaka Chiei , Wakabayashi Yasushi , Kanda Takahiro , Tawarahara Kei , Mutoh Masahiro , Matsunaga Masaki , Suwa Satoru , Takeuchi Yasuyo , Sakamoto Hiroki , Saito Hideki , Hayashi Kazusa , Wakahara Nobuyuki , Unno Kyoko , Ikoma Takenori , Sato Ryota , Iguchi Keisuke , Satoh Terumori , Sano Makoto , Suwa Kenichiro , Naruse Yoshihisa , Ohtani Hayato , Saotome Masao , Maekawa Yuichiro
Published: April 2024

Background

Hypertrophic cardiomyopathy (HCM) is often concomitant with sleep-disordered breathing (SDB), which can cause adverse cardiovascular events. Although an appropriate approach to SDB prevents cardiac remodelling, detection of concomitant SDB in patients with HCM remains suboptimal. Thus, we aimed to develop a machine learning-based discriminant model for SDB in HCM.

Methods

In the present multicentre study, we consecutively registered patients with HCM and performed nocturnal oximetry. The outcome was a high Oxygen Desaturation Index (ODI), defined as 3% ODI >10, which significantly correlated with the presence of moderate or severe SDB. We randomly divided the whole participants into a training set (80%) and a test set (20%). With data from the training set, we developed a random forest discriminant model for high ODI based on clinical parameters. We tested the ability of the discriminant model on the test set and compared it with a previous logistic regression model for distinguishing SDB in patients with HCM.

Results

Among 369 patients with HCM, 228 (61.8%) had high ODI. In the test set, the area under the receiver operating characteristic curve of the discriminant model was 0.86 (95% CI 0.77 to 0.94). The sensitivity was 0.91 (95% CI 0.79 to 0.98) and specificity was 0.68 (95% CI 0.48 to 0.84). When the test set was divided into low-probability and high-probability groups, the high-probability group had a higher prevalence of high ODI than the low-probability group (82.4% vs 17.4%, OR 20.9 (95% CI 5.3 to 105.8), Fisher’s exact test p<0.001). The discriminant model significantly outperformed the previous logistic regression model (DeLong test p=0.03).

Conclusions

Our study serves as the first to develop a machine learning-based discriminant model for the concomitance of SDB in patients with HCM. The discriminant model may facilitate cost-effective screening tests and treatments for SDB in the population with HCM.
SLESIS-R: an improved score for prediction of serious infection in patients with systemic lupus erythematosus based on the RELESSER prospective cohort
Authors: Rua-Figueroa Iñigo , García de Yébenes M Jesus , Martinez-Barrio Julia , Galindo Izquierdo Maria , Calvo Alén Jaime , Fernandez-Nebro Antonio , Menor-Almagro Raúl , Carmona Loreto , Tejera Segura Beatriz , Tomero Eva , Freire-González Mercedes , Sangüesa Clara , Horcada Loreto , Blanco Ricardo , Uriarte Itzazelaia Esther , Narváez Javier , Rosas Gómez de Salazar José Carlos , Gómez-Sabater Silvia , Morales Claudia Moriano , Andreu Jose L , Segarra Vicente Torrente , Aurrecoechea Elena , Perez Ana , Nóvoa Medina Javier , Salgado Eva , Lozano-Rivas Nuria , Montilla Carlos , Ruiz-Lucea Esther , Arevalo Marta , Iñiguez Carlota , García-Villanueva María Jesús , Exposito Lorena , Ibáñez-Barceló Mónica , Bonilla Gema , Carrión-Barberà Irene , Erausquin Celia , Fragio Gil Jorge Juan , Pecondón Angela , Toyos Francisco J , Cobo Tatiana , Muñoz-Jiménez Alejandro , Oller Jose , Nolla Joan M , Pego-Reigosa J M
Published: April 2024

Objective

To develop an improved score for prediction of severe infection in patients with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and to validate it in a large multicentre lupus cohort.

Methods

We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review. Performance was analysed using the C-statistic and the area under the receiver operating characteristic curve (AUROC). Internal validation was carried out using a 100-sample bootstrapping procedure. ORs were transformed into score items, and the AUROC was used to determine performance.

Results

A total of 1459 patients who had completed 1 year of follow-up were included in the development cohort (mean age, 49±13 years; 90% women). Twenty-five (1.7%) had experienced ≥1 severe infection. According to the adjusted multivariate model, severe infection could be predicted from four variables: age (years) ≥60, previous SLE-related hospitalisation, previous serious infection and glucocorticoid dose. A score was built from the best model, taking values from 0 to 17. The AUROC was 0.861 (0.777–0.946). The cut-off chosen was ≥6, which exhibited an accuracy of 85.9% and a positive likelihood ratio of 5.48.

Conclusions

SLESIS-R is an accurate and feasible instrument for predicting infections in patients with SLE. SLESIS-R could help to make informed decisions on the use of immunosuppressants and the implementation of preventive measures.
Psychological interventions targeting mental health and stress among females with cardiac disease: a scoping review
Authors: Susinski Stephanie , Bouchard Karen , Stragapede Elisa , Dozois Sophie , Sterling Evan , Tulloch Heather
Published: April 2024

Interventions that target mental health symptoms and stress among those with established cardiac disease have included predominately male samples despite female patients reporting greater severity of these symptoms. The aim of this scoping review was to synthesize the published literature on psychological interventions for females with cardiac disease. We conducted a systematic search of peer-reviewed randomized clinical trials (RCTs) published in the English language from 2003 to 2023, in three databases: Medline (Ovid), PsycInfo (Ovid), and CINAHL (EBSCO). Articles that included female samples, a control or comparison group, implemented psychological interventions, and measured depression, anxiety, or stress as an outcome were included in the review. Nine articles describing eight RCTs of psychological interventions, with a total of 1587 female patients with cardiac disease, were included. Interventions were most successful at reducing stress (75% of studies measuring stress reported efficacy), while symptoms of depression and anxiety were less responsive to intervention (∼30% of studies targeting these symptoms reported improvements) in comparison to a control condition. This scoping review highlights that further advancement in knowledge is required to better address the needs of females with cardiac disease and distress, particularly depression and anxiety.
Fast neutron production at the LNL Tandem from the $$^7$$Li($$^{14}$$N,xn)X reaction
Authors: Torres-Sánchez Pablo , Steiger Hans Th. J. , Mastinu Pierfrancesco , Wyss Jeffery L. , Kayser Lennard , Silvestrin Luca , Musacchio-González Elizabeth , Stock Matthias Raphael , Dörflinger David , Fahrendholz Ulrike , Prete Gianfranco , Carletto Osvaldo , Oberauer Lothar , Porras Ignacio
Published: April 2024

Fast neutron beams (E$$_n > $$

n

>

1 MeV) are of relevance for many scientific and industrial applications. This paper explores fast neutron production using a TANDEM accelerator at the Legnaro National Laboratories, via an energetic ion beam (90 MeV $$^{14}N$$

14

N

) onto a lithium target. The high energy models for nuclear collision of FLUKA foresee large neutron yields for reactions of this kind. The experiment aimed at validating the expected neutron yields from FLUKA simulations, using two separate and independent set-ups: one based on the multi-foil activation technique, and the other on the time of flight technique, by using liquid scintillator detectors. The results of the experiment show clear agreement of the measured spectra with the FLUKA simulations, both in the shape and the magnitude of the neutron flux at the measured positions. The neutron spectrum is centered around the 8 MeV range with mild tails, and a maximum neutron energy spanning up to 50 MeV. These advantageous results provide a starting point in the development of fast neutron beams based on high energy ion beams from medium-sized accelerator facilities.
The CompactLight Design Study
Authors: D’Auria G. , Adli E. , Aicheler M. , Aksoy A. , Alesini D. , Apsimon R. , Arnsberg J. , Auchettl R. , Bainbridge A. , Balazs K. , Bantekas D. , Bedolla J. , Behtouei M. , Bellaveglia M. , vd Berg M. , Bernhard A. , Bignami A. , Breitenbach M. , Breukers M. , Burt G. , Cai J. , Calvi M. , Cardelli F. , Carpanese M. , Cortes H. M. Castaneda , Castilla A. , Cianchi A. , Clarke J. , Cowie L. , Croia M. , Cross A. , Danailov M. , Dattoli G. , Deleval S. , Mitri S. Di , Diomede M. , Dowd R. , Dunning D. , Easton J. , Fang W. , Fatehi S. , Faus-Golfe A. , Ferianis M. , Ferrario M. , Ficcadenti L. , Gallo A. , Gazis E. , Gazis N. , Geometrante R. , Gethmann J. , Gioppo R. , Giribono A. , González-Iglesias D. , Goryashko V. , Grohmann S. , Gu Q. , Han Y. , Hinton A. , Hobi A. , Hoekstra R. , Huang X. , Jacewicz M. , Jones J. , Kaertner F. , Karagiannaki A. , Kokole M. , Kotitsa R. , Kotsopoulos D. , Krasch B. , Latina A. , Lepercq P. , Liu X. , Lucas T. G. , Luiten O. J. , Maheshwari M. , Mahnic J. , Mak A. , Marcos J. , Marin E. , Marinov K. , Martínez B. G. , Mercier B. , Migliorati M. , Milharcic T. , Mostacci A. , Mu noz R. , Musat V. , Mutsaers P. H. A. , Nergiz Z. , Nguyen F. , Nix L. , Palumbo L. , Parodi M. , Pavlica R. , Pellegrino L. , Pereira D. E. , Perez F. , Petralia A. , Piersanti L. , Pockar J. , Pramatari K. , Priem H. , Primozic U. , Rassool R. , Reiche S. , Revilak P. , Richter S. C. , Rochow R. , Rossi C. , Salén P. , Schmidt T. , Schoerling D. , Schulte D. , Scifo J. , Sheehy S. , Shepherd B. , Spataro B. , Stapnes S. , Stragier X. F. D. , Syratchev I. , Tabacco C. , Tan J. , Tanke E. , Taylor G. , Telahi I. , Thompson N. , Trachanas E. , Tzanetou K. S. , Vaccarezza C. , Vainola J. , Vannozzi A. , Volpi M. , Wang C. , Williams P. , Wu X. , Wuensch W. , Yap J. , Zangrando M. , Zhang K. , Zhang L. , Zhao Y. , Zhao Z. , Zhu D.
Published: April 2024

CompactLight is a Design Study funded by the European Union under the
Horizon 2020 research and innovation funding programme, with Grant Agreement No. 777431.
CompactLight was conducted by an International Collaboration of 23 international
laboratories and academic institutions, three private companies, and five third parties.
The project, which started in January 2018 with a duration of 48 months, aimed to design
an innovative, compact, and cost-effective hard X-ray FEL facility complemented by a
soft X-ray source to pave the road for future compact accelerator-based facilities. The
result is an accelerator that can be operated at up to 1 kHz pulse repetition rate,
beyond today’s state of the art, using the latest concepts for high brightness electron
photoinjectors, very high gradient accelerating structures in X-band, and novel
short-period undulators. In this report, we summarize the main deliverable of the
project: the CompactLight Conceptual Design Report, which overviews the current status
of the design and addresses the main technological challenges.
Computational investigation of the fundamental physical properties of lead-free halide double perovskite Rb2NaCoX6 (X = Cl, Br, and I) materials: Potential prospects for sustainable energy
Authors: Kumari Sunita , Rani Upasana , Rani Monika , Singh Rashmi , Kamlesh Peeyush Kumar , Kumari Sarita , Kumar Tanuj , Verma Ajay Singh
Published: April 2024

We have undertaken an ab initio investigation of emerging metal lead-free halide double perovskite materials for renewable energy applications using the WIEN2k simulation code. These materials have garnered significant attention from the research community due to their potential utility in electronic devices. Through an analysis of their electronic structure, we have ascertained that these materials exhibit characteristics of direct band gap semiconductors, falling within the energy range spanning 0.755 to 1.825[Formula: see text]eV. Furthermore, to check their suitability for use in photovoltaic devices, optical properties have been investigated. The thermoelectric potential of these materials has been explored using the BoltzTraP simulation code. The study of thermoelectric parameters indicates that the studied materials are effective thermoelectric materials with a strong potential for n-type doping. Additionally, thermodynamic parameters have been investigated to check their thermal stability, required to make them promising candidates for a wide range of renewable energy applications.
New soliton solutions of fractional Biswas–Milovic equation with Kerr, parabolic and cubic-quartic nonlinearities
Authors: Pekönür Esra , Akar Mutlu
Published: April 2024

This paper presents new explicit solutions of hyperbolic and trigonometric functions, obtained from the conformable fractional Biswas–Milovic equation, characterizing the long distance optical communications with three types nonlinearities: Kerr law, parabolic law and cubic-quartic ones. The Sardar sub-equation method is used, which gives the results that are of significant potential in a nonlinear system, providing a clear physical interpretation of the model under study. The resulting solutions are novel for the fractional Biswas–Milovic equation with the help of the method used, a powerful instrument for exploring precise solitary wave solutions for various other nonlinear equations in a nonlinear medium.
Effective self-power photodetector based on photogalvanic effect: A case study for Janus MoSSe-CrSSe lateral heterojunction
Authors: Wang Qiaohui , Li Hong , An Kang , Liu Fengbin , Lu Jing
Published: April 2024

The photogalvanic effect (PGE) can produce a photocurrent independent of a p–n junction or bias voltage, but the resulting photocurrent is usually very small. An appropriate lateral heterojunction can effectively enhance PGE. Here, we studied the PGE of a monolayer (ML) Janus MoSSe-CrSSe lateral heterojunction through ab initio quantum transport simulation. Compared with that of a homogeneous material, PGE is enhanced due to the reduced symmetry of the lateral heterojunction, and the maximum increase ratio in the photocurrent is more than two orders of magnitude greater than that of the homogeneous ML MoSSe and CrSSe photodetectors. A peak maximum photocurrent of 13.85 a[Formula: see text]/photon and high polarization sensitivity with a maximum extinction ratio of 308 are obtained for the ML MoSSe-CrSSe lateral heterojunction. These favorable properties indicate that the MoSSe-CrSSe lateral heterojunction is a promising candidate for photodetectors.
Graph Bipartization and Via Minimization for Intersection Graphs
Authors: Lin Lan , Lin Yixun
Published: April 2024

The graph bipartization problem, arising from via minimization in VLSI design and related areas, consists in finding a vertex subset [Formula: see text] of graph [Formula: see text] such that the induced subgraph [Formula: see text] is bipartite and [Formula: see text] is maximized. The problem has been proved to be NP-hard even for planar graphs and cubic graphs. On the other hand, the study of polynomial-time algorithms for typical graph classes is significant in both theoretical and applied aspects. This paper focuses on several intersection graph classes, such as line graphs, circular-arc graphs, and directed path graphs. For the line graphs, we show the NP-hardness results in general and present the polynomial-time algorithms for special cases. For circular-arc graphs and directed path graphs, we propose algorithms that improve on the previously known ones.
The Graft Transformation and Their Application on the Spectral Radius of Block Graphs
Authors: Zhu Yinfen , Chen Xu , Chen Xing
Published: April 2024

Let [Formula: see text] be a connected graph and [Formula: see text] be the adjacency matrix of [Formula: see text]. Suppose that [Formula: see text] are the eigenvalues of [Formula: see text]. In this paper, we first give a graft transformation on the spectral radius of graphs and then as their application, we determine the extremal graphs with maximum and minimum spectral radii among all clique trees. Furthermore, we also determine the unique graph with maximum spectral radius among all block graphs by using different methods.
Discussion of “Climate-Related Financial Risk: Insights from a Semisystematic Review of the Literature and Implications for Financial Reporting”
Authors: Dekeyser Simon
Published: April 2024

In this discussion of Griffin and Sun [( 2024 ), Climate-related Financial Risk: Insights from a Semisystematic Review of the Literature and Implications for Financial Reporting” the International Journal of Accounting, this issue], I examine both the incremental contribution of their work and its limitations. Furthermore, I delve into the limitations inherent in the chosen research design strategy and discuss how these limitations may affect some of the documented findings, particularly those related to accounting research.
Finite-Dimensional Stinespring Curves Can Approximate Any Dynamics
Authors: vom Ende Frederik
Published: April 2024

We generalize a recent result stating that all analytic quantum dynamics can be represented exactly as the reduction of unitary dynamics generated by a time- dependent Hamiltonian. More precisely, we prove that the partial trace over analytic paths of unitaries can approximate any Lipschitz-continuous quantum dynamics arbitrarily well. Equivalently, all such dynamics can be approximated by analytic Kraus operators. We conclude by discussing potential improvements and generalizations of these results, their limitations, and the general challenges one has to overcome when trying to relate dynamics to quantities on the system–environment level.
Principal Component Networks: Utilizing Low-Rank Activation Structure to Reduce Parameters Early in Training
Authors: Waleffe Roger , Rekatsinas Theodoros
Published: April 2024

Recent works show that overparameterized neural networks contain small subnetworks that exhibit comparable accuracy to the full model when trained in isolation. These results highlight the potential to reduce the computational costs of deep neural network training without sacrificing generalization performance. Initial approaches for finding these small networks relied on expensive multi-round train-and-prune procedures, limiting their practical potential, but more recent work identifies subnetworks using structured pruning techniques early in training. In this article, we study network activations, rather than network weights, and find that hidden layer activations in overparameterized networks exist primarily in subspaces smaller than the actual model width. We further notice that these subspaces can be identified early in training. Based on these observations, we show how to efficiently find small networks that exhibit similar accuracy to their overparameterized counterparts after only a few training epochs. We term these network architectures Principal Component Networks (PCNs). PCNs compress individual layers by retaining only the high variance linear combinations of channels—defined by the principal components of the layer inputs—a key difference from structured pruning techniques which focus on individual channel pruning using localized channel measurements. We evaluate PCNs on CIFAR-10 and ImageNet for VGG and ResNet style architectures and compare against existing methods for subnetwork identification during early training. We find that PCNs consistently reduce parameter counts with little accuracy loss, thus providing the potential to reduce the computational costs of deep neural network training. Beyond model compression, we also connect our observation regarding hidden layer activations to the feature representations learned by neural networks and discuss areas for future work.
HierCGRA: A Novel Framework for Large-scale CGRA with Hierarchical Modeling and Automated Design Space Exploration
Authors: Chen Sichao , Cai Chang , Zheng Su , Li Jiangnan , Zhu Guowei , Li Jingyuan , Yan Yazhou , Dai Yuan , Yin Wenbo , Wang Lingli
Published: April 2024

Coarse-grained reconfigurable arrays (CGRAs) are promising design choices in computation-intensive domains, since they can strike a balance between energy efficiency and flexibility. A typical CGRA comprises processing elements (PEs) that can execute operations in applications and interconnections between them. Nevertheless, most CGRAs suffer from the ineffectiveness of supporting flexible architecture design and solving large-scale mapping problems. To address these challenges, we introduce HierCGRA, a novel framework that integrates hierarchical CGRA modeling, Chisel-based Verilog generation, LLVM-based data flow graph (DFG) generation, DFG mapping, and design space exploration (DSE). With the graph homomorphism (GH) mapping algorithm, HierCGRA achieves a faster mapping speed and higher PE utilization rate compared with the existing state-of-the-art CGRA frameworks. The proposed hierarchical mapping strategy achieves 41× speedup on average compared with the ILP mapping algorithm in CGRA-ME. Furthermore, the automated DSE based on Bayesian optimization achieves a significant performance improvement by the heterogeneity of PEs and interconnections. With these features, HierCGRA enables the agile development for large-scale CGRA and accelerates the process of finding a better CGRA architecture.
Computing Random Forest-distances in the presence of missing data
Authors: Bicego Manuele , Cicalese Ferdinando
Published: April 2024

In this article, we study the problem of computing Random Forest-distances in the presence of missing data. We present a general framework which avoids pre-imputation and uses in an agnostic way the information contained in the input points. We centre our investigation on RatioRF, an RF-based distance recently introduced in the context of clustering and shown to outperform most known RF-based distance measures. We also show that the same framework can be applied to several other state-of-the-art RF-based measures and provide their extensions to the missing data case. We provide significant empirical evidence of the effectiveness of the proposed framework, showing extensive experiments with RatioRF on 15 datasets. Finally, we also positively compare our method with many alternative literature distances, which can be computed with missing values.
Automatic Extractive Text Summarization using Multiple Linguistic Features
Authors: Gupta Pooja , Nigam Swati , Singh Rajiv
Published: April 2024

Automatic text summarization (ATS) provides a summary of distinct categories of information using natural language processing (NLP). Low-resource languages like Hindi have restricted applications of these techniques. This study proposes a method for automatically generating summaries of Hindi documents using extractive technique. The approach retrieves pertinent sentences from the source documents by employing multiple linguistic features and machine learning (ML) using maximum likelihood estimation (MLE) and maximum entropy (ME). We conducted pre-processing on the input documents, such as eliminating Hindi stop words and stemming. We have obtained 15 linguistic feature scores from each document to identify the phrases with high scores for summary generation. We have performed experiments over BBC News articles, CNN News, DUC 2004, Hindi Text Short Summarization Corpus, Indian Language News Text Summarization Corpus, and Wikipedia Articles for the proposed text summarizer. The Hindi Text Short Summarization Corpus and Indian Language News Text Summarization Corpus datasets are in Hindi, whereas BBC News articles, CNN News, and the DUC 2004 datasets have been translated into Hindi using Google, Microsoft Bing, and Systran translators for experiments. The summarization results have been calculated and shown for Hindi as well as for English to compare the performance of a low and rich-resource language. Multiple ROUGE metrics, along with precision, recall, and F-measure, have been used for the evaluation, which shows the better performance of the proposed method with multiple ROUGE scores. We compare the proposed method with the supervised and unsupervised machine learning methodologies, including support vector machine (SVM), Naive Bayes (NB), decision tree (DT), latent semantic analysis (LSA), latent Dirichlet allocation (LDA), and K-means clustering, and it was found that the proposed method outperforms these methods.
SARDINE: Simulator for Automated Recommendation in Dynamic and Interactive Environments
Authors: Deffayet Romain , Thonet Thibaut , Hwang Dongyoon , Lehoux Vassilissa , Renders Jean-Michel , de Rijke Maarten
Published: April 2024

Simulators can provide valuable insights for researchers and practitioners who wish to improve recommender systems, because they allow one to easily tweak the experimental setup in which recommender systems operate, and as a result lower the cost of identifying general trends and uncovering novel findings about the candidate methods. A key requirement to enable this accelerated improvement cycle is that the simulator is able to span the various sources of complexity that can be found in the real recommendation environment that it simulates.

With the emergence of interactive and data-driven methods—e.g., reinforcement learning or online and counterfactual learning-to-rank—that aim to achieve user-related goals beyond the traditional accuracy-centric objectives, adequate simulators are needed. In particular, such simulators must model the various mechanisms that render the recommendation environment dynamic and interactive, e.g., the effect of recommendations on the user or the effect of biased data on subsequent iterations of the recommender system. We therefore propose SARDINE, a flexible and interpretable recommendation simulator that can help accelerate research in interactive and data-driven recommender systems. We demonstrate its usefulness by studying existing methods within nine diverse environments derived from SARDINE, and even uncover novel insights about them.
Structural, Mechanical and Thermal Behaviour of Graphene-Epoxy Polymer Matrix Nanocomposites
Authors: Awasthi Deepak , Paswan Manikant , Gupta Pallav
Published: April 2024

The change in characteristics in the microstructural features of epoxy nanocomposites created by reinforcing with graphene oxide (GO) obtained by controlled reduction of GO was investigated. The effects of adding various loadings (0.1–0.5 wt%) of RGO in epoxy resin were examined, with a focus on the material’s response toward mechanical and thermal properties. The robust interfacial bonding between epoxy resin and RGO is attributed to the higher surface area of the exfoliated layered geometry of graphene and is a key factor contributing to the enhanced physical properties in nanocomposite. The optimal incorporation of 2D nanofillers has been determined to induce a synergistic effect, thereby establishing a percolating network in thermal interface materials designed for high-performance electronic device.
Metformin mitigates adipogenesis of fibro-adipogenic progenitors after rotator cuff tears via activating mTOR/ULK1-mediated autophagy
Authors: Zhou Hao , Lin Xingzuan , Feng Shujing , Zhu Siyuan , Zhou Han , Chen Huifang , Youwu He , Wang Zekai , Wang Ru , Shao Xiexiang , Wang Jianhua
Published: April 2024

The current study demonstrated that gender-specific disparities in muscular fatty infiltration are attributed to mTOR/ULK1-mediated autophagy of FAPs. Decreased autophagic activity contributes to adipogenic differentiation in female FAPs after RCT. Moreover, metformin could enhance mTOR/ULK1-mediated autophagic processes of FAPs, thereby alleviating fatty infiltration and improving shoulder functionality after RCT. Therefore, metformin could be a promising noninvasive intervention to ameliorate muscular fatty infiltration of RCT.
Visceral adipose of obese mice inhibits endothelial inwardly rectifying K+ channels in a CD36-dependent fashion
Authors: Rokka Sabita , Sadeghinejad Masoumeh , Hudgins Emma C. , Johnson Erica J. , Nguyen Thanh , Fancher Ibra S.
Published: April 2024

Our findings suggest a role for visceral adipose tissue (VAT) in the dysfunction of endothelial Kir2.1 in obesity. We further reveal a role for CD36 as a major contributor to VAT-mediated Kir2.1 and endothelial dysfunction, suggesting that CD36 offers a potential target for preventing the early development of obesity-associated cardiovascular disease.
Evaluation of High-Performance Polyether Ether Ketone Polymer Treated with Piranha Solution and Epigallocatechin-3-Gallate Coating
Authors: Alsmael Mohammed A. , Al-Khafaji Aseel Mohammed
Published: April 2024

Background. Dental implantation has become a standard procedure with high success rates, relying on achieving osseointegration between the implant surface and surrounding bone tissue. Polyether ether ketone (PEEK) is a promising alternative to traditional dental implant materials like titanium, but its osseointegration capabilities are limited due to its hydrophobic nature and reduced surface roughness. Objective. The aim of the study is to increase the surface roughness and hydrophilicity of PEEK by treating the surface with piranha solution and then coating the surface with epigallocatechin-3-gallate (EGCG) by electrospraying technique. Materials and Methods. The study includes four groups intended to investigate the effect of piranha treatment and EGCG coating: a control group of PEEK discs with no treatment (C), PEEK samples treated with piranha solution (P), a group of PEEK samples coated with EGCG (E), and a group of PEEK samples treated with piranha solution and coated with EGCG (PE). Surface roughness, wettability, and microhardness were assessed through statistical analysis. Results. Piranha treatment increased surface roughness, while EGCG coating moderated it, resulting in an intermediate roughness in the PE group. EGCG significantly improved wettability, as indicated by the reduced contact angle. Microhardness increased by about 20% in EGCG-coated groups compared to noncoated groups. Statistical analysis confirmed significant differences between groups in all tests. Conclusion. This study demonstrates the potential of EGCG coating to enhance the surface properties of PEEK as dental implants. The combined piranha and EGCG modification approach shows promise for improved osseointegration, although further vivo research is necessary. Surface modification techniques hold the key to optimizing biomaterial performance, bridging the gap between laboratory findings and clinical implementation in dental implantology.