bluuebunny/crossref_metadata_2025 huggingface dataset:
Mortality and morbidity patterns in Yaoundé, Cameroon: An ICD-11 classification-based analysis
Authors: Nguefack-Tsague Georges , Lekeumo Fabrice Zobel Cheuyem , Noah Boris Edmond , Ndobo-Koe Valérie , Amani Adidja , Mekontchou Léa Melataguia , Gweth Marie Ntep , Assala Annick Collins Mfoulou Minso , Ngoufack Marie Nicole , Pierre René Binyom
Published: August 2023

Background
In Cameroon, data generated by health settings including morbidity and mortality parameters are not always uniform. In the absence of a national guideline necessary for the standardization and harmonization of data, precision of data required for effective decision-making is therefore not guaranteed.
Methods
The objective of the present investigation was to assess the reporting style of morbidity and mortality data in healthcare settings. A cross sectional study was carried out from May to June 2022 Yaoundé Central Hospital. A questionnaire was used to assess the need to set up a standard tool to improve the reporting system. Medical records were used to collect mortality and morbidity data which were then compared to the International Classification of Disease-11 (ICD-11) codification. Data were analysed using IBM-SPSS versions 26.
Results
Out of 200 patients’ morbidity causes recorded, more than two third were heterogeneous (74%). Almost half of mortality cause reported were heterogeneous (41%). Most of respondents stated the need to set up a standard tool for collecting mortality and morbidity data (82%). Although most of participants reported having sufficient knowledge to establish death certificates (83.6%), only a few proportions declared using medical certificated to establish cause of death (34.5%). Less than half of health staff were able to understand data flow (18%), correctly archive data (37%) and use electronic tool for data quality control (40%).
Conclusion
There was a high inadequacy between the hospital reporting style. It is therefore urgent that Cameroon national health authorities implement the ICD-11 in the data management system.
Physicians’ knowledge, attitudes, and beliefs regarding practices of male and female surgical sterilization procedures in Lebanon
Authors: Najdi Jad , Armache Alexandre , Chawareb Elia Abou , Heidar Nassib Abu , Zein Marwan , Fadel Anthony , Nehme Jimmy , Bachir Bassel
Published: August 2023

Objective Surgical sterilization, including vasectomy in males and tubal ligation in females, is a highly effective but underutilized contraception method. Adoption rates vary globally mostly due to misconceptions by both the general public and practicing physicians. Our survey aims to explore physicians' knowledge, attitudes and beliefs about surgical sterilization techniques.Study Design A web-based survey of four parts was sent to residents and attending physicians of different specialties in Lebanon between April 2022 and April 2023. 183 physicians responded to the survey. Data was analyzed using IBM SPSS Statistics. A descriptive analysis was performed using the chi-square test for categorical variables and ANOVA for continuous variables.Results Physicians specialized in Urology, OB/GYN, Family medicine and Internal medicine, filled the survey. The majority were resident physicians (79%), male (57%), single (72%) and did not receive training in family planning (73%). Knowledge assessment showed an average score of 5/7. After setting this as a passing score, 60.7% of participants passed the assessment with higher likelihood of passing among attending physicians (84.6%), OB/GYN physicians (94.4%), married participants (80.8%), and physicians who received training in family planning (91.8%). Recommendations varied among specialties, with urologists being more likely to recommend vasectomy depending on the clinical scenario (70–97%). Most physicians perceived the general public preferring tubal ligation as a sterilization method (98%).Conclusion Surgical sterilization is underutilized mostly due to lack of knowledge and cultural beliefs among practicing physicians in our region. Ongoing education is needed in medical training to promote family planning.
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images
Authors: Brima Yusuf , Atemkeng Marcellin
Published: August 2023

Deep learning shows promise for medical image analysis but lacks interpretability, hindering adoption in healthcare. Attribution techniques that explain model reasoning may increase trust in deep learning among clinical stakeholders. This paper aimed to evaluate attribution methods for illuminating how deep neural networks analyze medical images. Using adaptive path-based gradient integration, we attributed predictions from brain tumor MRI and COVID-19 chest X-ray datasets made by recent deep convolutional neural network models. The technique highlighted possible biomarkers, exposed model biases, and offered insights into the links between input and prediction. Our analysis demonstrates the method's ability to elucidate model reasoning on these datasets. The resulting attributions show promise for improving deep learning transparency for domain experts by revealing the rationale behind predictions. This study advances model interpretability to increase trust in deep learning among healthcare stakeholders.
In-silico anti–microbial, anti-inflammatory and hypoglycemic evaluation of active phytoconstituents of the plant: Leucas aspera (Willd.)
Authors: Islam Sariful , Bhagawati Hrishikesh , Tanjim Arifa , Mehboob Masayek , Sarma Mrinal Kashyap , Borah Chinmoyee , Islam Aminul , Basumatary Pankaj
Published: August 2023

Leucas aspera(willd.) (Labiatae family) is a dietary herb with a wide variety of biological activities, including antimicrobial activity. In this study, we usedin-silicodocking to see how well bioactive phytoconstituents fromL. asperamight operate against an inflammatory-triggering protein. Three phytoconstituents were selected from a list of thirty based on their ability to satisfy the Lipinski rule of five. Molsoft L.L.C. databases were used to forecast the drug-likeness score and adverse effects for the chosen compounds. SwissADME was used to make predictions about the pharmacokinetics and toxicological characteristics of the selected phytoconstituents. Docking studies were carried out using the PyRx to predict the binding affinity of the selected phytoconstituents with the protein from the protein data bank. Among the drugs tested, Leucasperol A had the highest drug-likeness score (-0.11) and Amyl propionate had the lowest (-1.24). In molecular docking investigations, the ligands were found to bind to the active site of the target protein with minimal binding energy values. In terms of binding affinities with the target proteins (4DX5 and 5V5Z), Leucasperol A had the highest (-8.8 kcal/mol & -8.6 kcal/mol) and Amyl propionate had the lowest (-4.5 kcal/mol & -4.5 kcal/mol). In terms of binding affinities with the target proteins (6LW5 and 1ILR), Leucasperol A had the highest (-8.7 kcal/mol & -7.5 kcal/mol) and Amyl propionate had the lowest (-5.2 kcal/mol & -4.1 kcal/mol). In terms of binding affinities with the target proteins (3BJM and 6LN2), Leucasperol A had the highest (-8.3 kcal/mol & -8.4 kcal/mol) and Amyl propionate had the lowest (-4.3 kcal/mol & -4.5 kcal/mol). Our results suggested that the phytochemicals we examined inL. asperamight have anti-microbial, anti-inflammatory & hypoglycaemic properties, suggesting that this plant might be useful as a treatment option.
Investigating post-traumatic syringomyelia and local fluid osmoregulation via a rat model
Authors: Pukale Dipak D. , Adkins-Travis Kayla , Aryal Siddhartha R. , Shriver Leah P. , Patti Gary J. , Leipzig Nic D.
Published: August 2023

Background The molecular etiology of syringomyelia (SM) post-spinal cord injury (SCI) is not well understood and only invasive surgical based treatments are available to treat SM. This study builds upon our previous omics studies andin vitrocellular investigations to further understand local fluid osmoregulation in post-traumatic SM (PTSM) to highlight important pathways for future molecular interventions. Methods A rat PTSM model consisting of a parenchymal injection of 2 µL quisqualic acid (QA) and an injection of 5 µL kaolin in the subarachnoid space, followed by laminectomy at the C7 to T1 level was utilized. 6 weeks prior to the initial surgery, parenchymal fluid and cerebrospinal fluid (CSF) were collected, and the osmolality analyzed. Immunohistochemistry (IHC), metabolomics analysis using LC/MS, and mass spectrometry-based imaging (MSI) were performed on injured and laminectomy only spinal cords. Results We demonstrated that the osmolality of the local parenchymal fluid encompassing syrinxes was higher compared to control spinal cords after laminectomy, indicating a local osmotic imbalance due to SM injury. Moreover, we also found that parenchymal fluid is more hypertonic than CSF, indicating establishment of a local osmotic gradient in the PTSM injured spinal cord (syrinx area) forcing fluid into the spinal cord parenchyma to form and/or expand syrinxes. IHC results demonstrated upregulation of betaine, ions, water channels/transporters, and enzymes (BGT1, KCC4, AQP1, AQP4, CHDH) at the injury site as compared to caudal and rostral sites to the injury, implying extensive local osmoregulation activities at the injury site. Further, metabolomics analysis corroborated alterations in osmolality at the injury site by upregulation of small molecule osmolytes including betaine, carnitine, glycerophosphocholine, arginine, creatine, guanidinoacetate, and spermidine. Conclusions In summary, PTSM results in local osmotic disturbance that propagates up to 6 weeks following initial injury. This coincides with and may contribute to syrinx formation/expansion.
Home-based arm cycling exercise improves trunk control in persons with incomplete spinal cord injury: an observational study
Authors: Helden Joeri F L van , Alexander Emma , Cabral Hélio V , Strutton Paul H , Martinez-Valdes Eduardo , Falla Deborah , Chowdhury Joy Roy , Chiou Shin-Yi
Published: August 2023

Arm cycling is used for cardiorespiratory rehabilitation but its therapeutic effects on the neural control of the trunk after spinal cord injury (SCI) remain unclear. We investigated the effects of single session of arm cycling on corticospinal excitability, and the feasibility of home-based arm cycling exercise training on volitional control of the erector spinae (ES) in individuals with incomplete SCI. Using transcranial magnetic stimulation, we assessed motor evoked potentials (MEPs) in the ES before and after 30 minutes of arm cycling in 15 individuals with SCI and 15 able-bodied controls (Experiment 1). Both groups showed increased ES MEP size after the arm cycling. The participants with SCI subsequently underwent a six-week home-based arm cycling exercise training (Experiment 2). MEP amplitudes and activity of the ES, and movements of the trunk during reaching, self-initiated rapid shoulder flexion, and predicted external perturbation tasks were measured. After the training, individuals with SCI reached further and improved trajectory of the trunk during the rapid shoulder flexion task, accompanied by increased ES activity and MEP amplitudes. Exercise adherence was excellent. We demonstrate preserved corticospinal drive after single arm cycling session and feasible home-based arm cycling exercise training for individuals with SCI for trunk rehabilitation.
Protocol for a randomized controlled trial of a psychoeducation material to reduce psychological distress levels in women with breast cancer post mastectomy in Indonesia
Authors: Mustikaningsih Dewi , Prajoko Yan Wisnu , Setyowibowo Hari , Anggorowati Anggorowati
Published: August 2023

BackgroundThe prevalence of post-mastectomy patients who experience symptoms of anxiety and depression are 40%, the impact of psychological stress due to mastectomy includes loss of self-confidence, specifically, body image, by 63%, lifestyle changes by 51.8%, feeling useless as much as 58% and feel less cared for by 75%. Patients who experience post-mastectomy stress may experience psychological side effects, including a 24% increased chance of cancer recurrence, a 30% increased risk of all-cause mortality, and a 29% greater risk of developing a particular type of breast cancer. The current study will examine whether our recently created nurse-guided psychoeducational material for Indonesian breast cancer survivors who have had mastectomy reduces psychological discomfort.MethodsIn Indonesia's Kariadi Hospital Semarang Centre Java, 84 patients will participate in a randomised controlled experiment. Data will be gathered at the start of the intervention (pre-assessment), 3 to 5 days later (post-assessment − 1), and 1 to 2 weeks later (follow-up assessment). The primary outcome is level of psychological distress and serotonin levels. Secondary outcomes are breast cancer post mastectomy score pain level, body image and fatigue.DiscussionIf effective, psychoeducation nurse-guided materials will be tested and put into practise in a variety of contexts for city local cares that offer health education/psychoeducation to women with breast cancer following mastectomy (such as in the hospital in West Java, Indonesia).Trial registrationTCTR20230501003. Date: Mei 1th,2023.
Brillouin light storage for 100 pulse widths
Authors: Stiller Birgit , Jaksch Kevin , Piotrowski Johannes , Merklein Moritz , Schmidt Mikolaj K. , Vu Khu , Ma Pan , Madden Stephen , Steel Michael , Poulton Christopher G. , Eggleton Benjamin
Published: August 2023

Signal processing based on stimulated Brillouin scattering (SBS) is limited by the narrow linewidth
of the optoacoustic response, which confines many Brillouin applications to continuous wave signals
or optical pulses longer than several nanoseconds. In this work, we experimentally demonstrate
Brillouin interactions at the 150 ps time scale and a delay for a record 15 ns which corresponds to a
delay of 100 pulse widths. This breakthrough experimental result was enabled by the high local gain
of the chalcogenide waveguides as the optoacoustic interaction length reduces with pulse width. We
successfully transfer 150ps-long pulses to traveling acoustic waves within a Brillouin-based memory
setup. The information encoded in the optical pulses is stored for 15 ns in the acoustic field. We
show the retrieval of eight amplitude levels, multiple consecutive pulses and low distortion in pulse
shape. The extension of Brillouin-based storage to the ultra-short pulse regime is an important step
for the realisation of practical Brillouin-based delay lines and other optical processing applications.
RT-Ranked: towards network resiliency by anticipating demand in TSCH/RPL communication environments.
Authors: Junior Ivanilson França Vieira , Granjal Jorge , Curado Marilia
Published: August 2023

Time-slotted Channel Hopping (TSCH) Media Access Control (MAC) was specified to target the Industrial Internet of Things needs. This MAC balances energy, bandwidth, and latency for deterministic communications in unreliable wireless environments. Building a TSCH schedule is arduous because the node negotiates cells with its neighbours based on queue occupancy, latency, and consumption metrics. The Minimal TSCH Configuration defined by RFC 8180 was specified for bootstrapping a 6TiSCH network and detailed configurations necessary to be supported. In particular, it adopts Routing Protocol for Low Power and Lossy networks (RPL) Non-Storing mode, which reduces the node's network awareness. Dealing with unpredicted traffic far from the forwarding node is difficult due to limited network information. Anticipating this unexpected flow from multiple network regions is essential because it can turn the forwarding node into a network bottleneck leading to high latency, packet discard or disconnection rates, forcing RPL to change the topology. To cope with that, this work proposes a new mechanism that implements an RPL control message option for passing forward the node's cell demand, allowing the node to anticipate the proper cell allocation for supporting the traffic originating by nodes far from the forwarding point embedded in Destination-Oriented Directed Acyclic Graph (DODAG) Information Object (DIO) and Destination Advertisement Object (DAO) RPL control messages. Implementing this mechanism in a distributed TSCH Scheduling developed in Contiki-NG yielded promising results in supporting unforeseen traffic bursts and has the potential to significantly improve the performance and reliability of TSCH schedules in challenging network environments.
Maxillary Sinus Ameloblastoma in Turner syndrome: A Comprehensive Case Report and Long-Term Follow-Up.
Authors: Maghous Abdelhak , Lalya Issam , marnouche El-Amin , Hommadi Mouhcine , Benlemlih Maroua , Zaghba Noha , Ennadif Ayoub , Bazine Amine , Andaloussi Khalid , Elmarjany Mohamed , Hadadi Khalid , sifat hassan
Published: August 2023

Maxillary sinus ameloblastoma is an uncommon locally aggressive odontogenic tumor. In this case report, we present a comprehensive long-term follow-up of maxillary sinus ameloblastoma occurring in a patient with Turner syndrome, managed through partial right maxillectomy followed by adjuvant operative bed radiotherapy.
Quantum spin liquid signatures in monolayer 1T-NbSe2
Authors: Wang Ye-Liang , Zhang Quanzhen , He Wen-Yu , Zhang Yu , Chen Yaoyao , Jia Liangguang , Hou Yanhui , Ji Hongyan , Yang Huixia , Zhang Teng , Liu Liwei , Gao Hong-Jun , Jung Thomas
Published: August 2023

Quantum spin liquids (QSLs) are in a quantum disordered state that is highly entangled and has fractional excitations. As a highly sought-after state of matter, QSLs were predicted to host spinon excitations and to arise in frustrated spin systems with large quantum fluctuations. Here we report on the experimental observation and theoretical modelling of QSL signatures in monolayer 1T-NbSe2, which is a newly emerging two-dimensional material that exhibits both charge-density-wave (CDW) and correlated insulating behaviors. By using scanning tunneling microscopy and spectroscopy (STM/STS), we confirm the presence of spin fluctuations in monolayer 1T-NbSe2 by observing the Kondo resonance as they interact with metallic 1H-NbSe2 monolayers. Subsequent STM/STS imaging of monolayer 1T-NbSe2 at the Hubbard band energy further reveals a long-wavelength charge modulation, in agreement with the spinon modulation expected for QSLs. By depositing manganese-phthalocyanine (MnPc) molecules with spin S = 3/2 onto monolayer 1T-NbSe2, new STS resonance peaks emerge at the Hubbard band edges of monolayer 1T-NbSe2. This observation is consistent with the spinon Kondo effect induced by a S = 3/2 magnetic impurity embedded in a QSL. Taken together, these experimental observations indicate that monolayer 1T-NbSe2 is a new promising QSL material.
A Reinforcement Method for Passenger Flow Control Based on Asynchronous Advantage Actor-Critic Neural Network
Authors: Wang Bao , Jin Peter J. , Luo Xia , Su Qiming
Published: August 2023

Effective passenger flow management is critical for improving service quality and alleviating congestion in metro networks. However, the dynamic nature of travel demand and the complex structure of metro networks present significant challenges in building and solving control models. Additionally, the high computational costs of existing methods limit their practical applications. To address these challenges, this study proposes a new reinforcement learning (RL) based method for passenger flow control. The method has three components: the network state characterization, the control model, and the reinforcement learning model. Then, the study outlines the “action”, “state”, and “reward” concepts in RL based on the definition of decision variables, constraints, and objective functions in the constructed passenger flow control programming model. An iterative interaction mechanism is introduced to synchronize the control schemes generated by the reinforcement learning unit and the network states. Furthermore, effectively utilizing computational resources, the Asynchronous Advantage Actor-Critic Neural Network (A3C-NN) is trained to optimize the complex programming model. Finally, the proposed approach is validated through a case study using data from Chengdu Urban Rail Transit (URT), demonstrating its effectiveness in achieving various objectives, such as minimizing passenger waiting time, maximizing passenger turnover, and maximizing passenger numbers.
Using logistic regression and random forest techniques to predict the degradation of forest roads
Authors: shabani saeid , ahmadi akram , mostafa mohsen , faramarzi hassan
Published: August 2023

The destruction of forest roads has significant adverse impacts on forest accessibility, resulting in heightened maintenance and environmental expenses, as well as posing potential threats to human life. Enhancing the sustainable and secure accessibility to forest regions necessitates a more comprehensive knowledge of the deterioration of forest pathways across temporal and spatial dimensions. The objective of this study is to utilize destruction prediction models to identify pertinent variables related to the state of the Hyrcanian forest road network in Golestan province. Additionally, the study aims to determine the most significant explanatory variables. To achieve the research objective, a set of 50 points were established along forest roads at a uniform distance of 200 meters from each other. The response variable, which pertains to the visibility of the forest road infrastructure, was recorded in binary format. Additionally, the explanatory variables were documented along a strip transect with a width of 10 meters perpendicular to the road. The study employed two conventional logistic regression models and a novel random forest model to forecast the deterioration of forest roads. Three indicators consist of TWI, natural ground gradient and cover density of cut slope, can predict road damage, as demonstrated by the implementation of two models. The random forest model exhibited superior accuracy to logistic regression, as evidenced by its success rate of 0.73 and prediction rate of 0.68. The results indicate that machine learning models offer significant insights into predicting road conditions and ensuring access to the Hyrcanian forests.
A generalization of a theorem of von Neumann
Authors: Eshkaftaki Ali Bayati
Published: August 2023

In 1953 von Neumann has proved that every n × n doubly substochastic matrix A can be increased to a doubly stochastic matrix, i.e., there is an n × n doubly stochastic matrix D for which A ≤ D. In this paper, we will discuss this result for a class of I × I doubly substochastic matrices. In fact, by a constructive method, we find an equivalent condition for existence of a doubly stochastic matrix D which satisfies A ≤ D, for all A ∈ A, where A is assumed a class of (finite or infinite) doubly substochastic matrices. Such a matrix D is called a cover of A. The uniqueness of the cover will also be discussed. Then we obtain an application of this concept to a system of (infinite) linear equations and inequalities.
MSC(2020): 15B48, 15B51, 15A45, 47A50
Filling the Gap Between ESG Discloser and Financial Performance in Indian Companies: The Moderating Role of the Sustainability Committee
Authors: Pasupuleti Akhil , Ayyagari Lakshmana Rao , Devarapalli Suman , Akuthota Sankar Rao
Published: August 2023

The present study aims to examine the impact of sustainable disclosure on firm performance, while considering the moderating role of the Sustainability Committee (SC) within the Indian business landscape. The sample size consists of 84 ESG-disclosing companies with 336 firm-year observations and employed correlation analysis, balanced panel data analysis with fixed effect method, and random effect method. The study has identified ESG disclosure and sustainability committees are significant and positively associated with profitability and firm performance, while moderate variables have received mixed results. To the best of the authors’ knowledge, this is the first research work to address a sustainability committee as a moderator in panel data analysis along with the support of two theories i.e., signaling and stakeholders theory. In the future, researchers may examine the possibility of advancements in this field, while acknowledging the significant role of green initiatives.
Investigating Hostile Post Detection in Gujarati: A Machine Learning Approach
Authors: Boda Jagruti
Published: August 2023

Hostile post on social media is a crucial issue for individual, government, and organizations. There is a critical need for an automated system that can investigate and identify hostile posts from large-scale data. In India, Gujarati is the sixth most spoken language. In this work, we have constructed a major hostile post dataset in the Gujarati language. The data are collected from Twitter, Instagram, and Facebook. Our dataset consists of 1,51,000 distinct tweets having 10,000 manually annotated posts. These posts are labeled into the Hostile and Non-Hostile categories. We have used the dataset in two ways: (i) Original Gujarati Text Data and (ii) Gujarati Data translated into English. We have also checked the performance of pre-processing and without pre-processing data by removing extra symbols and substituting emoji descriptions in the text. Finally, we have conducted experiments using machine learning models based on supervised learning such as Support Vector Machine, Decision Tree, Random Forest, Gaussian Naive-Bayes, Logistic Regression, K-Nearest Neighbor and unsupervised learning based model such as k-means clustering. We have evaluated performance of these models for Bag-of-Words and TF-IDF feature extraction methods. It is observed that classification using TF-IDF features is efficient. Among these methods Logistic regression outperforms with an Accuracy of 0.68 and F1-score of 0.67.
Clinical evolution of patients with pre-existing panic disorder during the COVID- 19 pandemic: Two-year longitudinal follow-up in Morocco
Authors: oumary Omar El , Lahlou Laila , Ouhamou Mina , Laaraj Hicham , Salehddine Zineb , McCormack Dawn , Doufik Jalal , Mouhadi Khalid , Rammouz Ismail
Published: August 2023

Background
Several studies have been conducted on the impact of the COVID-19 pandemic on the general population, but few have examined the longitudinal evolution of psychopathology in patients with mental health disorders at different stages of the pandemic. This study sought to answer these questions by assessing the trajectory of mental health in patients with pre-existing panic disorder in a COVID-19 pandemic setting while evaluating socio-demographic and clinical factors associated with outcomes.
Methods
This was a longitudinal study of panic disorder patients followed during three waves of the COVID-19 pandemic. Change assessed in mental health status used five validated scales: the Beck Depression Inventory-II (BDI-II), the Beck Anxiety Inventory (BAI), the Impact of Event Scale-revised (IES-R), The Mini International Neuropsychiatric Interview (MINI) for suicidal risk and the Panic Disorder Severity Scale Self Report version (PDSS-SR). Predictors of mental health symptom progression were assessed using multivariate analysis.
Results
There was a significant wave-to-wave reduction in depressive symptoms, post-traumatic stress, panic disorder severity and suicidal risk. Concerning anxiety symptoms, patients felt better and better during successive waves of the pandemic, with a statistically significant decrease from the first to the second wave of the COVID-19 pandemic. The analytical strategy also enabled the identification of the various socio-demographic and clinical factors likely to be associated with higher panic disorder severity.
Conclusion
It is timely to raise a series of questions that this research attempts to answer, and to develop personalized strategies for future pandemics in order to minimize the risk of aggravation or relapse in patients with panic disorder in particular, who may be more sensitive to multiple aspects of the pandemic.
Ambient Floor Vibration Sensing Advances Accessibility of Functional Gait Assessment for Children with Muscular Dystrophies
Authors: Dong Yiwen , Iammarino Megan , Liu Jingxiao , Codling Jesse , Fagert Jonathon , Mirshekari Mostafa , Lowes Linda , Zhang Pei , Noh Haeyoung
Published: August 2023

Muscular dystrophies (MD) are a group of genetic neuromuscular disorders that cause progressive weakness and loss of muscles over time, influencing 1 in 3500 to 5000 children worldwide. New and exciting treatment options have led to a critical need for a clinical post-marketing surveillance tool to confirm the efficacy and safety of these treatments after individuals receive them in a commercial setting. For MDs, functional gait assessment is a common approach to evaluate the efficacy of the treatments because muscle weakness is reflected in individuals' walking patterns. However, there is little incentive for the family to continue to travel for such assessments due to the lack of access to specialty centers. While various existing sensing devices, such as cameras, force plates, and wearables can assess gait at home, they are limited by privacy concerns, area of coverage, and discomfort in carrying devices, which is not practical for long-term, continuous monitoring in daily settings. In this study, we introduce a novel functional gait assessment system using ambient floor vibrations, which is non-invasive and scalable, requiring only low-cost and sparsely deployed geophone sensors attached to the floor surface, suitable for in-home usage. Our system captures floor vibrations generated by footsteps from patients while they walk around and analyzes such vibrations to extract essential gait health information. To enhance interpretability and reliability under various sensing scenarios, we translate the signal patterns of floor vibration to pathological gait patterns related to MD, and develop a hierarchical learning algorithm that aggregates insights from individual footsteps to estimate a person's overall gait performance. When evaluate through real-world experiments with 36 subjects (including 15 patients with MD), our floor vibration sensing system achieves a 94.8% accuracy in predicting functional gait stages for patients with MD. Our approach enables accurate, accessible, and scalable functional gait assessment, bringing MD progressive tracking into real life.
Prevalence, patterns, and impacts of multimorbidity on adverse clinical outcomes in chronic kidney disease
Authors: Chowdhury Samin
Published: August 2023

Background
Multimorbidity is the concurrent presence of two or more long-term health conditions in the same individual. It fragments healthcare delivery and affects quality of life. Chronic kidney disease (CKD) often occurs with multimorbidity. The prevalence of CKD is rising. However, there is a lack of evidence on the prevalence, patterns, and impacts of multimorbidity on adverse clinical outcomes in patients with CKD.
Methods
This was a systematically conducted literature review. A search was conducted in EMBASE, MEDLINE, CINAHL, and SCOPUS (2019–2023). The main search terms were “chronic kidney disease” and “multimorbidity.” The eligibility criteria were observational studies with adult participants with all stages of CKD (CKD stage 1–5 including those on renal replacement therapy). The exposure was multimorbidity quantified by measures. All-cause mortality, kidney disease progression, hospitalisation, and cardiovascular events were outcomes. The Joanna Briggs Institute (JBI) checklist was used for the risk of bias assessment. Due to heterogeneity in design and methods, Jennie Popay’s narrative synthesis was used for data synthesis.
Results
Of 6879 papers, nine papers met the inclusion criteria. Most studies included participants with all stages of CKD (CKD stage 1–5). The prevalence of multimorbidity ranged from 86.6–99.1%. Hypertension was the most prevalent comorbidity. The combination of concordant multimorbidity (hypertension, diabetes, and cardiovascular diseases) was highly prevalent. Multimorbidity was significantly associated with mortality, cardiovascular events, kidney disease progression, and hospitalisation. While older people had more multimorbidity burdens, younger patients with CKD were at a higher risk of death from multimorbidity. Severe CKD with clusters of cardiovascular diseases, diabetes, chronic pain, and depression was significantly associated with all-cause mortality.
Conclusion
There are associations between multimorbidity and adverse clinical outcomes in patients with CKD. However, there is a lack of data on Black, Asian, and Minority Ethnic participants and from low- and middle-income countries. Further research is needed to investigate the high prevalence of chronic pain and depression in chronic kidney disease.
The Impacts of Dimensionality, Diffusion, and Directedness on Intrinsic Cross-Model Simulation in Tile-Based Self-Assembly
Authors: Hader Daniel , Patitz Matthew
Published: August 2023

Motivated by applications in DNA-nanotechnology, theoretical investigations in algorithmic tile-assembly have blossomed into a mature theory. In addition to computational universality, the abstract Tile Assembly Model (aTAM) was shown to be intrinsically universal (FOCS 2012), a strong notion of completeness where a single tile set is capable of simulating the full dynamics of all systems within the model; however, this construction fundamentally required non-deterministic tile attachments. This was confirmed necessary when it was shown that the class of directed aTAM systems, those where all possible sequences of tile attachments result in the same terminal assembly, is not intrinsically universal (FOCS 2016). Furthermore, it was shown that the non-cooperative aTAM, where tiles only need to match on 1 side to bind rather than 2 or more, is not intrinsically universal (SODA 2014) nor computationally universal (STOC 2017). Building on these results to further investigate the other dynamics, Hader et al. examined several tile-assembly models which varied across (1) the numbers of dimensions used, (2) how tiles diffused through space, and (3) whether each system is directed, and determined which models exhibited intrinsic universality (SODA 2020). In this paper we extend those results to provide direct comparisons of the various models against each other by considering intrinsic simulations between models. Our results show that in some cases, one model is strictly more powerful than another, and in others, pairs of models have mutually exclusive capabilities. This paper is a greatly expanded version of that which appeared in ICALP 2023.
Fake News Detection through Graph-based Neural Networks: A Survey
Authors: Gong Shuzhi , Sinnott Richard , Qi Jianzhong , Paris Cecile
Published: August 2023

The popularity of online social networks has enabled rapid dissemination of infor- mation. People now can share and consume information much more rapidly than ever before. However, low-quality and/or accidentally/deliberately fake information can also spread rapidly. This can lead to considerable and negative impacts on society. Identifying, labelling and debunking online misinformation as early as possible has become an increasingly urgent problem.
Many methods have been proposed to detect fake news including many deep learning and graph-based approaches. In recent years, graph-based methods have yielded strong results, as they can closely model the social context and propagation process of online news. In this paper, we present a systematic review of fake news detection studies based on graph-based and deep learning-based techniques. We classify existing graph-based methods into knowledge-driven methods, propagation-based methods, and heterogeneous social context-based methods, depending on how a graph structure is constructed to model news related information flows. We further discuss the challenges and open problems in graph-based fake news detection and identify future research directions.
Nitrite excretion by cyanobacteria is controlled by the small protein NirP1
Authors: Hess Wolfgang , Kraus Alexander , Spät Philipp , Timm Stefan , Wilson Amy , Schumann Rhena , Hagemann Martin , Macek Boris
Published: August 2023

When the supply of inorganic carbon is limiting, photosynthetic cyanobacteria excrete nitrite, a toxic intermediate in the ammonia assimilation pathway from nitrate. While it has been hypothesized that the excreted nitrite represents excess nitrogen that could not be further assimilated due to the missing carbon, the underlying molecular mechanism has remained enigmatic. Here, we characterized a hitherto unannotated gene with homologs in the genomes of 485 different cyanobacteria that is upregulated under low carbon conditions and controlled by the transcription factor NtcA, a central regulator of nitrogen homeostasis. To understand its function, we ectopically overexpressed it in Synechocystis sp. PCC 6803, which resulted in a chlorotic phenotype, delayed growth, severe changes in amino acid pools, and nitrite excretion. Coimmunoprecipitation experiments revealed that this protein targets nitrite reductase, a central enzyme in the assimilation of ammonia from nitrate/nitrite, and was re-named to nitrite reductase regulator protein 1 (NirP1). Our results reveal that NirP1 is widely conserved in cyanobacteria and plays a crucial role in the coordination of C/N primary metabolism by targeting one of the central enzymes. In natural environments, the excreted nitrite will be utilized by other microorganisms; therefore, NirP1 ultimately impacts the activities and composition of the surrounding microbiome.
Extracellular vesicles from bodily fluids for the accurate diagnosis of Parkinson’s disease and related disorders: A systematic review and meta-analysis
Authors: Taha Hash Brown , Bogoniewski Aleksander
Published: August 2023

Parkinsonian disorders, including Parkinson's disease (PD), multiple system atrophy (MSA), dementia with Lewy body (DLB), corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are often misdiagnosed due to overlapping symptoms and the absence of precise biomarkers. Furthermore, there are no current methods to ascertain the progression and conversion of prodromal conditions such as REM behavior disorder (RBD). Extracellular vesicles (EVs), containing a mixture of biomolecules, have emerged as potential sources for parkinsonian diagnostics. However, inconsistencies in previous studies have left their diagnostic potential unclear. We conducted a meta-analysis, following PRISMA guidelines, to assess the diagnostic accuracy of general EVs isolated from various bodily fluids, including cerebrospinal fluid (CSF), plasma, serum, urine or saliva, in differentiating patients with parkinsonian disorders from healthy controls (HCs). The meta-analysis included 21 studies encompassing 1,285 patients with PD, 24 with MSA, 105 with DLB, 99 with PSP, 101 with RBD, and 783 HCs. Analyses were conducted only for patients with PD vs. HCs, given the limited number for other comparisons. Using bivariate and hierarchal receiver operating characteristics (HSROC) models, the meta-analysis revealed moderate diagnostic accuracy in distinguishing PD from HCs, with substantial heterogeneity and publication bias detected. The trim-and-fill method revealed at least two missing studies with null or low diagnostic accuracy. CSF-EVs showed better overall diagnostic accuracy, while plasma-EVs had the lowest performance. General EVs demonstrated higher diagnostic accuracy compared to CNS-originating EVs, which are more time-consuming, labor- and cost-intensive to isolate. In conclusion, while holding promise, utilizing biomarkers in general EVs for PD diagnosis remains unfeasible due to existing challenges. The focus should shift toward harmonizing the field through standardization, collaboration, and rigorous validation. Current efforts by ISEV aim to enhance the accuracy and reproducibility of EV-related research through rigor and standardization, aiming to bridge the gap between theory and practical clinical application.
Parental deprivation in early childhood impacts gene expression on brain development as a lifelong effect
Authors: Shinohara Haruka , Meguro-Horike Makiko , Inoue Takashi , Shimazu Miyuki , Hattori Machiko , Hibino Hitoshi , Fukasawa Kazumasa , Sasaki Erika , Horike Shin-ichi
Published: August 2023

Early life experiences, such as parental loss, neglect, and child abuse, are well-established risk factors for neurological disorders later in life, including depression, anxiety disorders, and post-traumatic stress disorder. However, the molecular mechanisms underlying the impact of adverse childhood experiences on neurophysiological systems throughout life remain incompletely understood. Common marmosets, which are non-human primates, typically give birth to 2–4 offspring, but only two usually survive. Therefore, human hand-rearing is employed to ensure the survival of the offspring. However, marmosets that are raised by humans often exhibit behavioral abnormalities, including abnormal vocalizations, excessive attachment to the caretaker, and aggressive behavior. Hence, our study aimed to investigate the hypothesis that human hand-rearing induces alterations in gene expression within the brains of infant marmosets, and that these changes persist into adulthood and are associated with behavioral abnormalities. Our analyses revealed consistent alterations in a subset of genes, including those related to neurodevelopmental diseases, across different developmental stages, indicating their continuous susceptibility to the effects of early parental deprivation. These findings highlight the dynamic nature of gene expression in response to early life experiences and suggest that the impact of early parental deprivation on gene expression may vary across different stages of development.
The Effect of Emotional Intelligence and Psychological Security on Digital Learning Readiness
Authors: Abdelfattah Fadi , ALAlawi Abrar , Mashaikhya Najla Yahya Al , Saleh Ayman AL
Published: August 2023

The purpose of this study is to examine the factors affecting students’ digital learning readiness, including emotional intelligence and student’s perceived psychological security as a mediator. The conceptual model has been drawn per the findings of previous studies. This study used quantitative data collected from one hundred thirty student via random sampling technique. Based on this study empirical investigation, the student’s digital readiness is significantly related to their emotional intelligence when dealing with digital learning. Moreover, this research highlights the critical mediating role of perceived psychological security in the relationship between emotional intelligence and digital learning readiness. This study will assist scholars, Higher Educational Institutions (HEIs), decision-makers, and practitioners in understanding and dealing with the learning mode changes from different perspectives, including the quality of the learning program and students’ psychological health.
Analyzing perceived caregiving burden and assessment of sociodemographic correlates among informal caregivers of Schizophrenia patients: a descriptive cross-sectional study
Authors: Qalb-I-Hyder Syed , Channa Summaira , Laghari Daryakhan , Moin Ghazal , Ansari Moin Ahmed , Qureshi Asra
Published: August 2023

Objective: Informal Caregivers experience various circumstances during patient care. Such instances could potentially lead to physical, emotional, and economical challenges. The aim of this study was to investigate caregiving burden among informal caregivers of schizophrenia patients and to find out factors that corroborate increment in caregiver’s burden. Participants and Methods: Schizophrenia patients and their informal caregivers were recruited from outpatient clinics of the largest public sector psychiatric hospital in the country. Data was collected on a pre-designed questionnaire through face-to-face interviews. Caregivers were evaluated for caregiving burden usingBurden Assessment Scale (BAS).Bivariate analysis and correlation coefficients were the focus methods of analysis to examine the association between burden of caregiving and corroborating factors. Results The mean age of Schizophrenia patients was 30.7 ± 10.3 years and, n:358(94%) were male. The mean age of informal caregivers was 42.3 ± 13.1 years and, 78% of them were male. The highest number of caregivers were parents n:156(41%) and the average duration of caregiving computed was 6.3 ± 4.9 years. The Mean Burden assessment Score (BAS) of caregivers was 49.6 ± 14.0 and 51% (n:196) of the caregivers were found with higher caregiving burden. Conclusion A strong advocacy support is needed at local level to offer social support and psychoeducational services for care providers. Additionally, it is crucial that such families or communities at large consider opportunities to identify that how support and task sharing for routine life responsibilities could help informal care providers to enjoy their role and contribute as an effective member of the society.
Construction and application of a cleaner production evaluation index system for the apple industry in China
Authors: Zhao Li , Shao Shuai , Wang Yingda , Gao Qiufeng , Zhang Yun , Bao Yining , Zhang Zhao
Published: August 2023

It is very important to establish a relatively complete evaluation index system for cleaner production in the apple industry in China. Based on interviews with apple experts, extensive apple industry data, and the national apple development plan and related national standards, this study constructed a CP evaluation index system for apples in China. The system included 6 first-grade indicators and 19 second-grade indicators of resource and energy consumption, product characteristics, production technology characteristics, pollutant generation, comprehensive utilisation of resources and cleaner production management. The weights of indicators at all levels were determined by analytic hierarchy processing and expert scoring, and a fuzzy comprehensive evaluation model and an accompanying two-tuple linguistic evaluation method were established. Finally, this study selected three apple orchards as case studies to verify the accuracy and feasibility of this index system, and based on the results of the evaluation, specific cleaner production improvement measures were proposed for the three orchards.