bluuebunny/crossref_metadata_2025_split huggingface dataset:
Faktor-Faktor yang memengaruhi Keakuratan Pemberian Code Diagnosa terhadap Pengklaiman BPJS di RSU Mitra Medika Tanjung Mulia
Authors: Mendrofa I’en Leflyanis 
Published: July 2024

Pendahuluan:Keakuratan coding adalah ketepatan pemberian kode yang dihasilkan oleh petugas coder sesuai pedoman penulisan kode ICD-10. Berdasarkan survey awal, terdapat sebanyak 30,7% kode diagnosa yang tidak akurat dari 1594 berkas rekam medis yang ter-pending saat verifikasi klaim selama tahun 2020. Penyebab ketidakakuratan kode diagnosa adalah petugas yang kurang teliti dalam menetapkan kode, ketidaklengkapan pemeriksaan penunjang, tulisan dokter yang sulit terbaca sehingga menyebabkan kesalahan pengkodingan dan adanya ketidaksesuaian alur pengkodingan diagnosa untuk klaim BPJS. Ketidakakuratan kode diagnosis ini akan membawa dampak besar terhadap pendapatan Rumah Sakit.Tujuan Penelitian:Untuk mengetahui Faktor-faktor yang memengaruhi keakuratan pemberian code diagnosa terhadap pengklaiman BPJS di RSU Mitra Medika Tanjung Mulia. Metode Penelitian:Penelitian Kualitatif bersifat deskriptif yang dilaksanakan mulai dari bulan Juli hingga Agustus 2021. Informan penelitian ini berjumlah lima orang yang diperoleh dengan teknik Purposive Sampling. Hasil Penelitian: terdapat faktor yang memengaruhi keakuratan kode diagnosa berdasarkan faktor man(manusia) yaitu pengetahuan, pendidikan, masa kerja, pelatihan petugas koding klaim dan yang seharusnya menjadi koder adalah perekam medis. Adanya kesesuaian persepsi antara dokter yang membuat diagnosa, koder yang menetapkan kode dan verifikator yang memeriksa klaim BPJS untuk Rumah Sakit, faktor material(bahan baku) yaitu kelengkapan berkas rekam medis, penunjang medis, dan tulisan dokter, faktor machine(mesin) yaitu ICD-10 revisi tahun 2010 untuk mengkode diagnosis utama dan diagnosis sekunder serta menggunakan ICD-9 revisi tahun 2010 untuk mengkode tindakan, faktor method(metode) yaitu pedoman seperti SPO, juknis INA-CBGs, dan evaluasi (audit) dalam pengklaiman.
Experimental Study on Phytoremediation of Heavy Metal from Mine Wastewater by Rumex nepalensis Spreng.
Authors: TECHANE GERA , GEBRE GEREMEW SAHILU , AMARE ELFU 
Published: July 2024

Tailings pond is considered as the main source of heavy metal pollution in gold mining areas. These heavy metals are directly released into fresh water without proper treatment. Phytoremediation process with the selected terrestrial plants may be an alternative solution for the mine wastewater treatment. In the current study, an experimental investigation found that Rumex nepalensis Spreng. has found a good accumulator of multi-metals in 15 days of experimental period. The results revealed that the removal efficiencies for Zn, Cu, Ni and Pb were 100%, 92%, 87%, and 67%, respectively. These indicate the plant showed its maximum accumulation of multi-metals. However, Pb reached saturation at the end of the 10th day, which makes its removal efficiency only in the first 10 days of the experimental period. The experiment revealed Pb and Ni which were above WHO standard for drinking water in the mine wastewater were made to permissible limit for these metals after the treatment.
Orchids of UNIMAS: Diversity in a Developed Campus Landscape
Authors: ABD MUTALIB ALMUNAH , MOHD RAFFI MOHD AKMAL , KALU MEEKIONG , NORDIN FARAH ALIA 
Published: July 2024

For the past three decades, various biotic components in Universiti Malaysia Sarawak (UNIMAS) natural habitats have been studied but less attention given to the largest family of flowering plants, the Orchidaceae. A preliminary survey in the campus areas has resulted in the discovery of more than ten species of orchids. Therefore, in this study more field samplings were conducted throughout the UNIMAS campus focusing on the developed areas to unveil the potential of UNIMAS-developed areas as a growth ground for orchids. To date, 37 orchid species have been recorded from these areas; mainly found on the planted trees at the roadside and landscaped areas surrounding the academic buildings, while the terrestrial species were found to inhabit different types of disturbed habitat. Among them, Dendrobium pensile was identified as a new record to Sarawak while Dendrobium pseudostriatellum and Pinalia biglandulosa were endemic to Borneo. This study provides an insight into the orchid resiliency towards habitat alteration, landscape phorophytes species that can host orchids, and management of species in a developed landscape.
A GESTÃO DE REDES SOCIAIS E VANTAGENS DE MARKETING DE CONTEÚDO PARA O MERCADO DE SORVETES
Authors: Lima Assis Geovana , DE MENDONÇA BARROS MALLU 
Published: July 2024

O sorvete é uma sobremesa que atrai o paladar de crianças, adultos e idosos de todas as idades e nacionalidades, nos mais diferentes horários ou estações do ano. Somado a isso, o marketing de conteúdo refere-se a uma abordagem que envolve criar e distribuir conteúdo relevante e útil para um público-alvo, com o objetivo de gerar conexão, melhorar a autoridade e promover ações que resultem em lucro dos negócios por meio das redes sociais. Assim, esta pesquisa busca atender aos seguintes objetivos: identificar os motivos pelos quais o segmento de sorveterias contratam os serviços de uma agência de marketing de conteúdo, definir e caracterizar marketing de conteúdo, apresentar as formas de comunicação como vantagens e estratégias de marketing de conteúdo digital aplicado aos negócios especializados na comercialização de sorvetes. Pretende-se responder a seguinte questão problema: quais são os motivos estratégicos que impulsionam a decisão de uma empresa a contratar o serviço de marketing de conteúdo para suas redes sociais? Tendo como hipótese que os gestores que optam por contratar serviços de marketing de conteúdo para suas empresas buscam obter reconhecimento e autoridade para suas marcas. Como procedimento metodológico, esta pesquisa foi estruturada em duas fases para atender aos objetivos do estudo. A primeira fase consiste em uma revisão da literatura, abordando uma pesquisa bibliográfica de caráter descritivo e exploratório. Por fim, o presente trabalho buscou apresentar curiosidades acerca da história e negócio de sorvetes e a relevância das estratégias de marketing de conteúdo como produção de valor para pessoas e empresas e relacionamento com o cliente.
Deconstructing demographic bias in speech-based machine learning models for digital health
Authors: Yang Michael , El-Attar Abd-Allah , Chaspari Theodora 
Published: July 2024

IntroductionMachine learning (ML) algorithms have been heralded as promising solutions to the realization of assistive systems in digital healthcare, due to their ability to detect fine-grain patterns that are not easily perceived by humans. Yet, ML algorithms have also been critiqued for treating individuals differently based on their demography, thus propagating existing disparities. This paper explores gender and race bias in speech-based ML algorithms that detect behavioral and mental health outcomes.MethodsThis paper examines potential sources of bias in the data used to train the ML, encompassing acoustic features extracted from speech signals and associated labels, as well as in the ML decisions. The paper further examines approaches to reduce existing bias via using the features that are the least informative of one’s demographic information as the ML input, and transforming the feature space in an adversarial manner to diminish the evidence of the demographic information while retaining information about the focal behavioral and mental health state.ResultsResults are presented in two domains, the first pertaining to gender and race bias when estimating levels of anxiety, and the second pertaining to gender bias in detecting depression. Findings indicate the presence of statistically significant differences in both acoustic features and labels among demographic groups, as well as differential ML performance among groups. The statistically significant differences present in the label space are partially preserved in the ML decisions. Although variations in ML performance across demographic groups were noted, results are mixed regarding the models’ ability to accurately estimate healthcare outcomes for the sensitive groups.DiscussionThese findings underscore the necessity for careful and thoughtful design in developing ML models that are capable of maintaining crucial aspects of the data and perform effectively across all populations in digital healthcare applications.
Risk stratification and prediction of severity of COVID-19 infection in patients with preexisting cardiovascular disease
Authors: Matejin Stanislava , Gregoric Igor D. , Radovancevic Rajko , Paessler Slobodan , Perovic Vladimir 
Published: July 2024

IntroductionCoronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 is a highly contagious viral disease. Cardiovascular diseases and heart failure elevate the risk of mechanical ventilation and fatal outcomes among COVID-19 patients, while COVID-19 itself increases the likelihood of adverse cardiovascular outcomes.MethodsWe collected blood samples and clinical data from hospitalized cardiovascular patients with and without proven COVID-19 infection in the time period before the vaccine became available. Statistical correlation analysis and machine learning were used to evaluate and identify individual parameters that could predict the risk of needing mechanical ventilation and patient survival.ResultsOur results confirmed that COVID-19 is associated with a severe outcome and identified increased levels of ferritin, fibrinogen, and platelets, as well as decreased levels of albumin, as having a negative impact on patient survival. Additionally, patients on ACE/ARB had a lower chance of dying or needing mechanical ventilation. The machine learning models revealed that ferritin, PCO2, and CRP were the most efficient combination of parameters for predicting survival, while the combination of albumin, fibrinogen, platelets, ALP, AB titer, and D-dimer was the most efficient for predicting the likelihood of requiring mechanical ventilation.ConclusionWe believe that creating an AI-based model that uses these patient parameters to predict the cardiovascular patient’s risk of mortality, severe complications, and the need for mechanical ventilation would help healthcare providers with rapid triage and redistribution of medical services, with the goal of improving overall survival. The use of the most effective combination of parameters in our models could advance risk assessment and treatment planning among the general population of cardiovascular patients.
Observation of intracranial artery and venous sinus hemodynamics using compressed sensing-accelerated 4D flow MRI: performance at different acceleration factors
Authors: Cao Jiajun , Yuan Chang , Zhang Yukun , Quan Yue , Chang Peipei , Yang Jing , Song Qingwei , Miao Yanwei 
Published: July 2024

ObjectiveTo investigate the feasibility and performance of 4D flow MRI accelerated by compressed sensing (CS) for the hemodynamic quantification of intracranial artery and venous sinus.Materials and methodsForty healthy volunteers were prospectively recruited, and 20 volunteers underwent 4D flow MRI of cerebral artery, and the remaining volunteers underwent 4D flow MRI of venous sinus. A series of 4D flow MRI was acquired with different acceleration factors (AFs), including sensitivity encoding (SENSE, AF = 4) and CS (AF = CS4, CS6, CS8, and CS10) at a 3.0 T MRI scanner. The hemodynamic parameters, including flow rate, mean velocity, peak velocity, max axial wall shear stress (WSS), average axial WSS, max circumferential WSS, average circumferential WSS, and 3D WSS, were calculated at the internal carotid artery (ICA), transverse sinus (TS), straight sinus (SS), and superior sagittal sinus (SSS).ResultsCompared to the SENSE4 scan, for the left ICA C2, mean velocity measured by CS8 and CS10 groups, and 3D WSS measured by CS6, CS8, and CS10 groups were underestimated; for the right ICA C2, mean velocity measured by CS10 group, and 3D WSS measured by CS8 and CS10 groups were underestimated; for the right ICA C4, mean velocity measured by CS10 group, and 3D WSS measured by CS8 and CS10 groups were underestimated; and for the right ICA C7, mean velocity and 3D WSS measured by CS8 and CS10 groups, and average axial WSS measured by CS8 group were also underestimated (all p &lt; 0.05). For the left TS, max axial WSS and 3D WSS measured by CS10 group were significantly underestimated (p = 0.032 and 0.003). Similarly, for SS, mean velocity, peak velocity, average axial WSS measured by the CS8 and CS10 groups, max axial WSS measured by CS6, CS8, and CS10 groups, and 3D WSS measured by CS10 group were significantly underestimated compared to the SENSE4 scan (p = 0.000–0.021). The hemodynamic parameters measured by CS4 group had only minimal bias and great limits of agreement compared to conventional 4D flow (SENSE4) in the ICA and every venous sinus (the max/min upper limit to low limit of the 95% limits of agreement = 11.4/0.03 to 0.004/−5.7, 14.4/0.05 to −0.03/−9.0, 12.6/0.04 to −0.03/−9.4, 16.8/0.04 to 0.6/−14.1; the max/min bias = 5.0/−1.2, 3.5/−1.4, 4.5/−1.1, 6.6/−4.0 for CS4, CS6, CS8, and CS10, respectively).ConclusionCS4 strikes a good balance in 4D flow between flow quantifications and scan time, which could be recommended for routine clinical use.
The clinical effect of sevoflurane anesthesia with laryngeal mask airway in the extraction of teeth in children
Authors: Wang Bin , Han Minglin 
Published: July 2024

ObjectiveTo evaluate the effect of sevoflurane general anesthesia with laryngeal mask airway in the extraction of teeth.MethodsA retrospective analysis was performed on 88 children who underwent extraction of teeth in the Department of Anesthesiology of our hospital from June 2022 to April 2023, including 44 patients who received traditional anesthesia as the control group and 44 patients who received laryngeal mask airway sevoflurane general anesthesia as the observation group. Anesthesia and operation records of patients in the two groups were analyzed, including intraoperative vital signs, anesthesia induction time, recovery time of spontaneous breathing, first feeding time within 24 h after surgery, postoperative pain score, incidence of adverse reactions, Ramsay score and wake agitation, and other indicators were collected, and statistical analysis was conducted.ResultsThe recovery time of the observation group was 7.88 ± 4.95 min, and the recovery time of spontaneous respiration was 10.58 ± 3.64 min, which were significantly shorter than 15.23 ± 5.12 min and 14.41 ± 3.56 min of the control group (P &lt; 0.001). There were no significant differences between the two groups in anesthesia induction, operation duration and first feeding time within 24 h after operation (P &gt; 0.05). There was no significant difference in postoperative pain scores between the two groups (P &gt; 0.05). The overall incidence of adverse reactions was 6.82% in the observation group compared with 22.73% in the control group (χ² = 4.423, P = 0.035). In addition, the Ramsay score of the observation group was significantly improved compared with the control group (P &lt; 0.05), and the incidence of agitation during the recovery period was also significantly decreased (P &lt; 0.05).ConclusionLaryngeal mask airway sevoflurane anesthesia can significantly accelerate the recovery process of children after extraction of teeth, and reduce the occurrence of adverse reactions, providing a safer and more efficient choice than traditional anesthesia.
The association between symptoms of developmental coordination disorder and neuropsychological characteristics in children with and without ADHD
Authors: Lee Taeyeop , Lim Jongseok , Kim Seonok , Kim Jichul , Park Kee Jeong , Joung Yoo-Sook , Kim Hyo-Won 
Published: July 2024

ObjectiveAttention-deficit/hyperactivity disorder (ADHD) frequently co-occurs with developmental coordination disorder (DCD). This study aimed to evaluate the association between DCD symptoms and neuropsychological characteristics in children with and without ADHD.MethodsWe recruited 298 children aged 5–12 years. Motor performance was assessed using the Developmental Coordination Disorder Questionnaire (DCDQ), while ADHD symptoms were assessed using the ADHD Rating Scale (ARS) and the Advanced Test of Attention (ATA). Cognitive characteristics were measured using the Wechsler Intelligence Scale, and behavioral characteristics were assessed using the Korean Personality Rating Scale for Children.ResultsThe children had a mean age of 7.6 ± 1.7 years, with 214 (71.8%) being boys. Among children diagnosed with ADHD (n = 176), 39.2% exceeded the DCDQ cutoff score, compared to 4.1% in the neurotypical group (n = 122). In the correlation analysis, the DCDQ total score was significantly correlated with ARS, omission and commission errors in visual and auditory ATA, and full-scale intellectual quotient. In addition, symptoms of depression, social dysfunction, and psychosis were correlated with the DCDQ total score. In the between-group analysis, children with both ADHD and DCD exhibited more omission errors on the auditory ATA and behavioral problems related to depression, social dysfunction, and psychosis compared to children with ADHD only.ConclusionOur study indicates that children with ADHD exhibit more difficulties in motor performance. Children with both ADHD and DCD may present with a greater burden of psychiatric conditions than children with ADHD only, suggesting the need for careful monitoring in clinical practice.
The validity and reliability of a hydraulic resistance device for assessing resisted sprint time
Authors: Sašek Matic , Cvjetičanin Oskar , Šarabon Nejc 
Published: July 2024

IntroductionThe aim of this study was to assess the validity and reliability of a hydraulic resistance device (HRD) for monitoring sprint split times under different loads within and between sessions.MethodsThree 20-m sprints with low (15 N), medium-low (40 N), medium-high (50 N), and high (130 N) HRD resistance levels (loads) were performed on two separate occasions 14 days apart. Twenty-four student athletes (24.8 ± 3.8 years) participated in the first session and 13 (24.1 ± 3.2 years) of them in the second session. Resisted sprints split times over a distance of 0–20 m (t0–5, t0–10, t0–20, t5–10, t10–15, t15–20) were measured simultaneously with magnetic incremental encoder embedded in the HRD and a system of single-beam timing gates.ResultsThe results showed acceptable to high within session (ICC3,1 = 0.91–0.99; CV = 0.92%–3.38%) and between session (ICC3,1 = 0.82–0.99; CV = 1.62%–4.84%) reliability of HRD for measuring all split times at all loads. The minimal detectable change between sessions ranged from 3.3% at high load to 9.9% at low load. The HRD systematically underestimated timing gates times at all loads (bias = 2.01–11.08%), yet good to excellent consistency was observed between the HRD and timing gates, specifically for t0–10 and t0–20 (ICC3,k lower 95% CI = 0.84–0.99).DiscussionDue to high reliability and good validity in monitoring resisted sprint times, the HRD holds potential for practical and research applications.
A Volume-Adjustable Artificial Womb for Extremely Preterm Infants
Authors: Heyer Jan , Schubert Franziska , Seitz Alexander L. , Steinle Yannick , Arens Jutta , Orlikowsky Thorsten , Steinseifer Ulrich , Schmitz-Rode Thomas , Jansen Sebastian V. , Schoberer Mark 
Published: July 2024

More than 13 million children are born preterm annually. Prematurity-related mortality accounts for 0.9 million deaths worldwide. The majority of those affected are Extremely Preterm Infants (gestational age less than 28 weeks). Immaturity causes organ failure and specific morbidities like germinal matrix hemorrhage, bronchopulmonary dysplasia, and necrotizing enterocolitis. Artificial womb and placenta technologies address these issues. As a bridge-to-life technology, they provide a liquid environment to allow organ maturation under more physiological conditions. The proposed artificial womb can adapt to fetal growth. Volume adjustment is achieved by removing fluid from the interspace between an inner and outer chamber. Results of the in vitro tests showed a temperature constancy of 36.8°C ± 0.3°C without pressure loss over 7 days. The volume of the inner sac was variable between 3.6 and 7.0 L. We designed a filtration and disinfection system for this particular purpose. This system has proven strong disinfection capabilities, effective filtering of metabolic waste, and the ability to avoid phospholipid washout. The presented artificial womb has sufficient volume variability to adapt to the physiologic growth of an extremely preterm neonate over a 4-week period. We regard this as an important step in the development of this bridge-to-life technology.
Machine Learning Techniques for Blind Beam Alignment in mmWave Massive MIMO
Authors: Ktari Aymen , Ghauch Hadi , Rekaya-Ben Othman Ghaya 
Published: July 2024

This paper proposes methods for Machine Learning (ML)-based Beam Alignment (BA), using low-complexity ML models, and achieves a small pilot overhead. We assume a single-user massive mmWave MIMO, Uplink, using a fully analog architecture. Assuming large-dimension codebooks of possible beam patterns at UE and BS, this data-driven and model-based approach aims to partially and blindly sound a small subset of beams from these codebooks. The proposed BA is blind (no CSI), based on Received Signal Energies (RSEs), and circumvents the need for exhaustively sounding all possible beams. A sub-sampled subset of beams is then used to train several ML models such as low-rank Matrix Factorization (MF), non-negative MF (NMF), and shallow Multi-Layer Perceptron (MLP). We provide an extensive mathematical description of these models and the algorithms for each of them. Our extensive numerical results show that, by sounding only 10% of the beams from the UE and BS codebooks, the proposed ML tools are able to accurately predict the non-sounded beams through multiple transmitted power regimes. This observation holds as the codebook sizes at UE and BS vary from 128×128 to 1024×1024.