Miracle-dz/UniFAR-FTUs huggingface dataset:
Artemether and Quinine are Safe and Effective in The Treatment of Severe Malaria in Nigerian Children

Severe malaria is a medical emergency. Parenteral artesunate is recommended over quinine for severe malaria. Artemether, is an alternative to parenteral artesunate in certain settings. The study was designed to compare the efficacy and safety of quinine with artermether using an open randomized trial in a paediatric ward of a specialist care center. Thirty-two patients with severe malaria were randomly assigned to receive either artemether, 3.2mg/kg start and 1.6 mg/kg body weight intramuscularly daily for 4 days or quinine, 10mg/kg body weight in 5% dextrose/saline intravenously 8 hourly till recovery from coma or able to take oral dose. Patients were followed up for 14 days. Mean fever clearance time for quinine was significantly lower when compared with artemether, (46.5 ± 20.5 versus 72.00 ± 27.7 hours; P =0.006). The malaria parasite clearance time was however significantly lower with artemether than with quinine (31.5 ± 14.5 versus 46.5 ± 6.00 hours; P=0.001). Adverse events, including tinnitus and insomnia in quinine group were generally mild. There was no adverse effect observed with artemether. Quinine and artemether were both effective and safe in the treatment of severe malaria in children. Artemether was better tolerated, cleared parasite faster with earlier and sustained recovery from anaemia, jaundice and coma
The recipient perspective: a mixed methods Inquiry of knowledgeseeking factors in tacit knowledge contexts

Tacit knowledge is an important source of competitive advantage to organisations. Sharing tacit knowledge among employees is vital to realising its benefits. Knowledge sharing requires the effective provision of knowledge and the useful acquisition of knowledge. More recently, knowledge seeking has been proposed as an additional recipient behaviour which encourages the provider to share their knowledge. Additionally, research has acknowledged the important role individual and social factors play in influencing the knowledge sharing. However, whether those factors equally effect recipient knowledge seeking and acquisition has been under-investigated. To address these gaps, this research investigates the individual and social factors which influence interpersonal knowledge seeking by knowledge workers engaged in highly tacit tasks within two separate contexts. In addition, knowledge seeking as a strategy for effective tacit knowledge acquisition is explored. Study one uses interviews with 33 knowledge-workers to explore individual and social factors which influence their tacit knowledge seeking, acquisition and sharing. Study two surveyed 233 junior doctors to test direct and indirect relationships between individual and social factors and their tacit knowledge seeking and acquisition from consultant doctors. The key findings support the contention that the individual and social factors which effect knowledge seeking are not interchangeable with those that effect knowledge acquisition and sharing. Various individual and social factors effect knowledge seeking at different stages of this behaviour. Furthermore, findings indicate that knowledge seeking can enhance successful acquisition of tacit knowledge through the organisational learning process of interpreting. This is the first study to compare individual and social factors which influence behaviours of seeking, acquisition and sharing in one study. It is also the first to empirically examine the 4i framework, and specifically the mediating effect of interpreting to explain the relationship between knowledge seeking and acquisition. Both studies provide actionable insights to improve successful knowledge sharing practices for tacit tasks.
Wetland dependency drives temporal turnover of bird species between high‐ and low‐water years in floodplain wetlands of the Paraná River

Temporal turnover of species between predominantly aquatic and terrestrial phases of floodplains, a process that helps maintain the high bird diversity of river–floodplain systems, could be driven by dependency of species on wetlands. To assess this, we compared the bird assemblages of river–floodplain systems at 60 sites along the Paraná River during the nonbreeding seasons of 2011, when water levels were predominantly high (high‐water year), and 2012, when levels were predominantly much lower (low‐water year). Birds were sampled by point counts repeated four times during each year at each site. We tested whether temporal patterns differed between wetland‐dependent and nonwetland‐dependent birds because these groups show positive and negative relationships, respectively, with water‐level increases. Species composition varied between years. Ten of the 14 species associated with high water levels in 2011 were waterbirds, and 11 of the 14 species associated with lower water levels (2012) were nonwetland species. Species richness and abundance per site of waterbirds and abundance of wetland species were higher during the high‐water year than in the low‐water year. Species richness, abundance, and diversity per site of nonwetland birds were, on the other hand, higher during the low‐water year than in the high‐water year. Species turnover between predominantly high‐ and low‐water periods did not respond to shorter term water‐level fluctuations within each year. In conclusion, our results show that degree of wetland dependence drives bird species turnover as a function of water‐level fluctuations, showing the importance of hydrological variability for bird conservation in river–floodplain systems.
Centralized Resource Allocation Latency of SideLink Communication in NR V2X

This paper investigates centralized resource allocation latency in the New Radio Vehicle-to-Everything (NR V2X) Mode 1. It presents a new resource partitioning technique among Road Side Units (RSUs) supervised by a cellular base station called Partial Time Reuse (PTR) in a highway scenario. This technique divides the vehicle’s transmission period (broadcast periodicity) into two intervals for two adjacent RSUs. Each RSU divides its interval duration into two shorter intervals used by vehicles located in central and edge RSU coverage areas to increase the frequency reuse distance and decrease the resource re-allocation delays. Furthermore, we proposed the Centralized-Estimation and Reservation Resource Allocation (CERRA) algorithm as an alternative resource allocation method to the Configured Grant (CG) method proposed by the 3rd Generation Partnership Project (3GPP). C-ERRA works by listing all addresses of resources that will be accessible in an estimated period using a decremental Re-selection Counter (RC). The cellular base station generated RC value in each resource (re)allocation. PTR performance is compared with another spectrum partitioning technique termed Partial Frequency Reuse Technique (PFR), which divides the spectrum instead of time. However, C-ERRA performance with PTR shows excellent results compared with CG with PFR in re-allocation delay. C-ERRA with PTR and PFR has displayed promising results in frequency ruse distance and packet reception ratio.
Handling Method of Imbalance Data for Machine Learning : Focused on Sampling

Recently, more and more attempts have been made to solve the problems faced by academia and industry through machine learning. Accordingly, various attempts are being made to solve non-general situations through machine learning, such as deviance, fraud detection and disability detection. A variety of attempts have been made to resolve the non-normal situation in which data is distributed disproportionately, generally resulting in errors. In this paper, we propose handling method of imbalance data for machine learning. The proposed method to such problem of an imbalance in data by verifying that the population distribution of major class is well extracted. Performance Evaluations have proven the proposed method to be better than the existing methods. ■ keyword :∣Imbalance Data∣Machine Learning∣Under Sampling∣Over Sampling∣Anomaly Detection∣ * 이 논문은 2017년도 정부(과학기술정보통신부)의 재원으로 한국연구재단-차세대정보・컴퓨팅기술개발사업(No. NRF-2017M3C4A7069432), 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원(No. 2019R1A2C2084257), 그리 고 2019년도 정부(과학기술정보통신부)의 재원(No.B0101-15-0266, 실시간 대규모 영상 데이터 이해·예측을 위한 고성능 비 주얼 디스커버리 플랫폼 개발)의 지원을 받아 수행된 연구임 접수일자 : 2019년 08월 23일 수정일자 : 2019년 10월 11일 심사완료일 : 2019년 10월 11일 교신저자 : 유재수, e-mail : yjs@chungbuk.ac. kr 한국콘텐츠학회논문지 '19 Vol. 19 No. 11 568 라 머신러닝은 점점 더 중요해지고 있다. 특히, 머신러 닝에 기반을 두어서 분류 예측하는 문제는 산업계에서 널리 사용되고 있다. 분류 예측 문제에서 가장 흔하게 만나는 문제는 데이터 불균형 문제이다. 데이터 불균형 문제는 사기 탐지, 허가되지 않은 네트워크 침입 탐지, 장애 탐지, 의료 진단 등 다양한 분야에서 데이터가 불 균형하게 분포하여 발생하는 문제를 의미한다. 또한 클 래스란 분류의 기준이 되는 대상 데이터를 의미한다. 예를 들어, 클래스는 사기 탐지에서는 사기 유무, 네트 워크 침입 탐지에서는 침입 유무, 장애 탐지에서는 장 애 유무 등을 구분할 수 있는 데이터이다. 또한 데이터 의 수가 많은 클래스를 다수 클래스(Major Class)라 하 고 데이터의 수가 적은 클래스를 소수 클래스(Minor Class)라 정의한다. 데이터 불균형 문제의 가장 큰 문제는 데이터 분류 예측 시 기계 학습에 부정적인 영향을 준다는 것이다. 의사 결정모형이나 신경망 모형은 훈련 데이터 셋이 등 급 간 균일하게 분포한다고 가정한다[1]. 그러나 위에서 서술한대로 사기 탐지, 허가되지 않은 네트워크 침입 탐지, 장애 탐지, 의료 진단 등 실제 세상에서 발생하는 많은 분류 예측 문제들은 등급 간 데이터가 균일하게 분포하지 않으며 비율 또한 매우 낮은 경우가 대다수이 다. 이러한 데이터 불균형 문제는 오류를 야기하게 된 다[1]. 이러한 데이터 불균형 문제를 극복하기 위해 다 양한 기법들이 연구되고 있다[1-11]. 주로 데이터를 균 형 있게 조작하는 데이터 수준 방법(Data-level approach)과 보다 클래스 불균형에 민감하게 반응하 는 알고리즘 수준 방법이 존재한다. 데이터 불균형이 초래하는 오류를 극복하기 위해 시 도된 방법 중 데이터 레벨 접근 방법은 데이터 불균형 으로 인해 발생되는 원인을 제거하여 문제를 해결하는 방법이다. 즉, 데이터 레벨 접근 방법은 데이터를 균형 있게 맞추어 학습을 시키는 방법이다. 데이터 레벨 접 근방법은 크게 두 가지 접근 방향을 가진다. 첫째는 샘 플링 방법이다. 샘플링은 소수 클래스의 데이터를 다수 클래스만큼 증폭시키는 오버 샘플링과 다수 클래스를 소수 클래스만큼 감소시키는 언더 샘플링으로 구성되 며 일반적으로 대표적인 오버 샘플링에는 랜덤 오버 샘 플링(ROS), 소수 클래스 오버 샘플링(SMOTE)이 존재 하며, 언더 샘플링에는 랜덤 언더 샘플링(RUS)이 존재 한다. 두 번째는 피쳐 셀렉션(Feature selection) 방법이 다. 데이터의 고차원성과 관련성 없는 피쳐들은 불균형 데이터셋에서 분류기의 성능을 저하시키고 잘못 분류 되는 비율을 증가시키기 때문에 피쳐 셀렉션이 필요하 다[1]. Zheng et al[6]에서는 피쳐 셀렉션 기법들인 information gain, chi square, correlation oefficient, odds ratio을 명시적으로 결합한 피쳐 셀 렉션을 사용했다. 본 논문에서는 머신러닝을 위한 불균형 데이터 처리 방법을 제안한다. 제안하는 기법은 데이터 레벨 접근 방법을 개선한 실무에 적합한 샘플링 방법을 제안한다. 제안하는 방법은 샘플링 방법을 중심으로 다수 클래스 (Major Class)의 모집단 분포를 효율적으로 추출하도 록 검증하여 머신 러닝을 위한 불균형 데이터 문제를 해결한다. 본 논문의 구성은 다음과 같다. 2절에서는 관련연구 를 조사 분석한다. 3절에서는 제안하는 샘플링 기법을 기술한다. 4절에서는 성능평가를 통해 제안하는 기법의 타당성을 보인다. 5절에서는 결론 및 향후 연구를 설명 한다.
EPISTOP – INTERNATIONAL, LONG-TERM, PROSPECTIVE STUDY EVALUATING CLINICAL AND MOLECULAR BIOMARKERS OF EPILEPTOGENESIS IN A GENETIC MODEL OF EPILEPSY – TUBEROUS SCLEROSIS COMPLEX

Epileptogenesis is barely studied in humans, as patients usually present AFTER the seizure onset. EPISTOP is the first prospective study of epileptogenesis in humans, beginning BEFORE seizures and continuing through age 2+ years, permitting detailed analysis of the onset, drug-resistance, and comorbidities of epilepsy in a homogenous group of patients with prenatal or early infantile diagnosis of Tuberous Sclerosis Complex (TSC). Project is funded by European Union within 7 th Frame Programme. AIM: The aim of EPISTOP is to examine the biomarkers of epilepsy and to identify possible new therapeutic targets to block or otherwise modify epileptogenesis in humans. METHODS: Biomarker analysis will be performed by a multidisciplinary, comprehensive approach which consists of: 1/ prospective study of epilepsy development in infants with TSC, including analysis of clinical, neuroimaging, and molecular, blood-derived biomarkers at predefined time points; 2/ prospective study of blood-based biomarkers in infants with TSC treated with antiepileptic drugs prior to seizure onset in comparison to children treated only after clinical seizures appearance; 3/ analysis of biomarkers of epileptogenesis and drug-resistant epilepsy in brain specimens obtained from TSC patients who have had epilepsy surgery and TSC autopsy cases. RESULTS: EPISTOP should permit to confirm or discover role of genes and proteins involved in the epileptogenesis. The mechanisms of drug-resistancy should be also elucidated. CONCLUSION: EPISTOP is the first project aimed to assess the epileptogenesis in humans.
Microbe‐Dependent Exacerbated Alveolar Bone Destruction in Heterozygous Cherubism Mice

Cherubism (OMIM#118400) is a craniofacial disorder characterized by destructive jaw expansion. Gain‐of‐function mutations in SH3‐domain binding protein 2 (SH3BP2) are responsible for this rare disorder. We have previously shown that homozygous knock‐in (KI) mice (Sh3bp2 KI/KI) recapitulate human cherubism by developing inflammatory lesions in the jaw. However, it remains unknown why heterozygous KI mice (Sh3bp2 KI/+) do not recapitulate the excessive jawbone destruction in human cherubism, even though all mutations are heterozygous in humans. We hypothesized that Sh3bp2 KI/+ mice need to be challenged for developing exacerbated jawbone destruction and that bacterial stimulation in the oral cavity may be involved in the mechanism. In this study, we applied a ligature‐induced periodontitis model to Sh3bp2 KI/+ mice to induce inflammatory alveolar bone destruction. Ligature placement induced alveolar bone resorption with gingival inflammation. Quantification of alveolar bone volume revealed that Sh3bp2 KI/+ mice developed more severe bone loss (male: 43.0% ± 10.6%, female: 42.6% ± 10.4%) compared with Sh3bp2 +/+ mice (male: 25.8% ± 4.0%, female: 30.9% ± 6.5%). Measurement of bone loss by the cement‐enamel junction–alveolar bone crest distance showed no difference between Sh3bp2 KI/+ and Sh3bp2 +/+ mice. The number of osteoclasts on the alveolar bone surface was higher in male Sh3bp2 KI/+ mice, but not in females, compared with Sh3bp2 +/+ mice. In contrast, inflammatory cytokine levels in gingiva were comparable between Sh3bp2 KI/+ and Sh3bp2 +/+ mice with ligatures. Genetic deletion of the spleen tyrosine kinase in myeloid cells and antibiotic treatment suppressed alveolar bone loss in Sh3bp2 KI/+ mice, suggesting that increased osteoclast differentiation and function mediated by SYK and accumulation of oral bacteria are responsible for the increased alveolar bone loss in Sh3bp2 KI/+ mice with ligature‐induced periodontitis. High amounts of oral bacterial load caused by insufficient oral hygiene could be a trigger for the initiation of jawbone destruction in human cherubism. © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.
Microfluidic-based Growth and Imaging of Bacterial Biofilms

Biofilms are a ubiquitous form of growth for bacteria on surfaces in most environments, natural or manmade. Here we present a protocol using the Bioflux microfluidic system to investigate the organized structure and development of these multicellular communities. Microfluidic systems present an opportunity to grow biofilms in a stable, physiologically maintained environment that is readily observable via time-lapse microscopy.
Proline metabolism-related gene expression in four potato genotypes in response to drought stress

Drought severely limits potato yield. The aim of this work was to study a response of plantlets of four potato genotypes to polyethylene glycol (PEG 6000)-induced drought stress in both physiological and molecular levels. The drought-tolerant and drought-sensitive genotypes were identified based on plantlet growth, chlorophyll content, lipid peroxidation, free proline content, and proline metabolism-related gene expressions. We found that PEG-induced stress increased malondialdehyde (MDA) and proline content, and drought-tolerant plantlets exhibited lower MDA and proline content than sensitive genotypes. In addition, PEG up-regulated ∆-1-pyrroline-5-carboxylate synthase (P5CS) and pyrroline- 5-carboxylate reductase (P5CR) gene expressions and down-regulated pyrroline dehydrogenase (PDH) and ∆-1-pyrroline-5-carboxylate dehydrogenase (P5CDH) gene expressions. Genotype B plantlets exhibited lower P5CS and P5CR expressions and higher PDH and P5CDH expressions compared with the other plantlets. The results suggest that significant cultivar differences among potato plantlets in response to PEG-induced drought stress are exhibited in root length, MDA content, proline accumulation, and proline metabolism-related gene expressions.
Design of an aperture measuring device for nuclear power plant

Due to the complex working environment, the traditional measurement methods cannot achieve accurate measurement. Firstly, based on the principle of pneumatic measurement, the mechanical structure of the measuring device in the end plug is designed; Secondly, aiming at the strong irradiation environment of the internal warp measuring device, a crawler underwater mobile platform is designed, and a fully automatic positioning and walking algorithm is proposed combined with GIS system; Finally, the statistical algorithm is used to improve the measurement accuracy of the inner diameter of the end plug. The modular design of the device not only improves the detection accuracy, but also enhances the applicability of the detection device and expands the application range of the aperture measurement device. Thermocouple is a key component in the core measurement system of nuclear power plant. At present, the success rate of thermocouple replacement in China is low, and its replacement difficulty is often caused by the blockage of thermocouple conduit. In view of the above problems, a robot which can work at the bottom of reactor in high radiation environment, narrow working space and weak acidic water is designed. Combined with the functional requirements and environment of the robot, the driving scheme and detection scheme are demonstrated, and the feasibility of the design is proved. In this paper, the structural design and electrical design are also completed, and the image recognition is optimized through the algorithm, so that the operator can remotely and accurately control the motion of the robot. Finally, it not only solves the problem of underwater detection, but also lays the foundation for underwater research robot development.
Congenital defect of craniovertebral junction in twins with Kniest dysplasia â case report

Kniest dysplasia is a rare disease from the group of osteochondrodysplasias, rated type II colagenopathies, and like other skeletal dysplasias may be associated with defects of cranio-vertebral junction with atlanto-axial instability. Objects: a case of spontaneous atlantoaxial subluxation with spinal canal narrowing at the level of craniovertebral junction in twins with Kniest dysplasia was presented. Methods: on the basis of clinical examination, radiographs and MRI study, children were qualified for operative treatment - posterior widening of the foramen magnum and occipito-cervical fusion with titanium anchors. During control examination 4 years after primary surgery, patients was very active, without any neurological deficits, x-ray pictures and MRI study revealed widening of the foramen magnum and full fusion in the place of surgery. Conclusion: authors suggestion is that in the case of foramen magnum and spinal canal narrowing, operative treatment with decompression of nervous structures and stabilization should be advised.
Potential Information Security Risks in The Implementation of AI - Based Systems

At present, technological solutions based on artificial intelligence (AI) are being accelerated in various sectors of the economy and social relations in the world. Practice shows that fast-developing information technologies, as a rule, carry new, previously unidentified threats to information security (IS). It is quite obvious that identification of vulnerabilities, threats and risks of AI technologies requires consideration of each technology separately or in some aggregate in cases of their joint use in application solutions. Of the wide range of AI technologies, data preparation, DevOps, Machine Learning (ML) algorithms, cloud technologies, microprocessors and public services (including Marketplaces) have received the most attention. Due to the high importance and impact on most AI solutions, this paper will focus on the key AI assets, the attacks and risks that arise when implementing AI-based systems, and the issue of building secure AI.
Role of protein dynamics in enthalpy-driven recognition of topologically distinct dsRNAs by dsRBDs

Taking leads from the fact that a handful of double-stranded RNA-binding domains (dsRBDs) interact with a massive number of topologically distinct double-stranded RNAs (dsRNAs) in crucial biological pathways, and to understand the adaptability required by dsRBDs to target the pool of dsRNA substrates, we employed two independent model dsRBDs in an ITC and NMR spectroscopy based study. Our previous study revealed the presence of microsecond timescale dynamics in RNA-binding regions in the two dsRBDs studied. In the current study, results from ITC-based titrations showed that the binding of dsRBD with topologically distinct dsRNAs is enthalpy-driven, with each dsRNA-dsRBD pair having distinct combination of enthalpy-entropy yielding a similar change in free energy upon RNA-binding. We also show that the each of the dsRNA, used in this study, binds to the dsRBD in a unique mode. Further, intrinsic conformational exchange present in the RNA-binding regions of the apo-dsRBD was shown to quench upon binding with a dsRNA, while conformational exchange got induced at the residues that are in close proximity to where exchange was present in the apo-protein. This apparent relay of conformational exchange from one site to the other site upon dsRNA-binding thus suggests the importance of intrinsic dynamics to adapt to target a variety of dsRNA-shapes. Statement of Significance This study reports that the interaction between dsRBDs and dsRNAs is enthalpy-driven, is perturbed by subtle changes in dsRNA shapes, and exhibits a classic case of enthalpy-entropy compensation. Further, the intrinsic microsecond timescale conformational exchange present in the apo-dsRBD was observed to get quenched upon RNA-binding. An apparent relay of conformational exchange was also observed from quenched sites to spatially proximal sites upon RNA-binding, suggesting highly adaptive nature of the dsRBD, a critical feature required to target topologically distinct dsRNA.
Diabetic Neuropathy: Discordance between Symptoms and Electrophysiological Testing in Saudi Diabetics

Objective: To determine the prevalence of nerve conduction velocity alteration in symptomatic diabetic neuropathy and to report the associated risk factors. Method: A cross sectional study of Saudi diabetics followed up in the medical outpatient clinic at King Abdulaziz University Hospital between January 1998 to May 1999. Diabetic neuropathy was diagnosed using the Michigan Neuropathy Program. Patients included in the study were those who had symptomatic neuropathy and scored >2 on simple clinical examination. Nerve conduction studies were done, detailed information of each patients age, sex, Body Mass Index (BMI), type and duration of diabetes, mode of treatment, degree of glycemic control, presence of hypertension, hyperlipidemia and smoking were recorded. Results: A total of 136 patients were included in the study with mean age of 56.2 years and mean duration of diabetes 12.49 years. Normal nerve conduction studies were found in 36% of the patients. Patients using insulin , prolonged and poorly controlled diabetes were the most important risk factors associated with diabetic neuropathy (p<0.001). Conclusion: The discordance between symptoms and nerve conduction studies means that we need nerve conduction studies for the proper diagnosis of diabetic neuropathy. Prolonged, poorly controlled diabetes and insulin use were risk factors associated with diabetic neuropathy. Aggressive/strict control of blood glucose is the key in the ultimate prevention of diabetic neuropathy.