bluuebunny/crossref_metadata_2025 huggingface dataset:
جُهود إمارة الشَّارقة في تَطْوِير وتَحْدِيث الْمَتَاحِف
Authors: الظهوري علي , ابوالعينين عمادالدين
Published: December 2023

لقد تَناول هذا البحث بالدراسة والتَّحليل لجُهود إحدى الإمارات التي لها دَور هام وبصمة عظيمة في تَطْوِير وتَحْدِيث العَديد من الْمَتَاحِف  مثل إمارة الشَّارقة التي تُعد شَاهِدة علي حضارة دولة الإمارات والتي تَحتوي على العَديد من الآثار الهامة والتُّراث الإنساني العَريق، وقد حَرَصت حكومة الشَّارقة علي الاِهتمام بهذا التُّراث وتَطْوِيره بصورة مُستمرة ، كما اِهتمت بتَطْوِير مُختلف المؤسَّسات ذات الصِّلة الوَثيقة به ، وذلك إيمانًا بأهمية مَكانته التَّاريخيَّة علي مَر العصور فكان من الضَّروري أن تَترسخ مَكانته ومَنزلته في ذهن الأجيال المُختلفة عَبر الأزمنة ، وهو الأمر الذي أدَّى إلي قيام حُكومة الشَّارقة بجهود عَظيمة في تَطْوِير قِطاع الْمَتَاحِف لِمَّا يُمثِّله من أهمية كُبرى  لمحاولة حفظ هذا التُّراث وآثار مُتنوعة عَبَّر عن تاريخ الدولة وعَراقتها، وقد اِعتمد الباحث في هذا البحث على المنهج الوصفي التحليلي بهدف وصف وتحليل جُهود إمارة الشَّارقة ، وأثر ذلك في دَعْم وتَطْوِير قِطاع الْمَتَاحِف ، كما تَمَّ الاِعتماد على المنهج الاِستقرائي في مُحاولة لاِستقراء الدراسات السابقة التي تَناولت جهود الإمارة في دَعْم قِطاع الْمَتَاحِف وما تَحْتَوِيه من آثار تَاريخيَّة عريقة.
ولقد تَوصلت الدراسة إلي نَتائج عَديدة منها: أن لإمارة الشَّارقة موقع جُغرافي مُتميز وبيئات مُتنوعة وتاريخ وحَضارة عريقة ألقت بظِلالها علي جَذب السَائِحين من مُختلف دول العالم وقد أَخذت حُكومة الشَّارقة علي عَاتقها بناء المَزيد من الْمَتَاحِف وتَطْوِيرها وتَحْدِيثها بصورة مُستمرة ، كما كان للهيئات الحُكوميَّة دورًا هامًا في تَطْوِير الْمَتَاحِف ورَقابتها ومدي مُلائمتها لمعايير الجُودة العالميَّة .
خصائص الأحياء السكنية وأثرها على جودة حياة القاطنين في ضاحية الخالدية بإمارة الشارقة
Authors: العقروبي حمده , أبو الخير أميمة
Published: December 2023

تناولت الدراسة خصائص الأحياء السكنية في إمارة الشارقة وأثرها على جودة حياة المواطنين القاطنين فيها من خلال مؤشرات البيئة السكنية والبنية التحتية ومؤشرات المرافق الخدمية، وتم اختيار ضاحية الخالدية وهي أحد الأحياء السكنية بإمارة الشارقة لإجراء الدراسة الميدانية،واستخدمت الدراسة منهج المسح الإجتماعي، وتم جمع البيانات والمعلومات بالإعتماد على أداتين رئيسيتين وهي الملاحظة كون الباحثة من القاطنين في الضاحية،ودليل المقابلة المتعمقة الذي طبق خلال اجراء المقابلات مع أفراد من أسر المواطنين المقيمين في الضاحية للتعرف على مدى رضاهم عن الحياة في الضاحية وتطلعاتهم المستقبلية.وقد هدفت الدراسة إلى التعرف على خصائص الضاحية وأثرها على جودة حياة أفراد العينة من الناحية الإجتماعية والصحية والنفسية.وخلصت نتائج الدراسة إلى أن(88%)من أفراد العينة يرون أن البيئة السكنية والبنية التحتية والمرافق الخدمية أثرت بشكل كبير على جودة حياتهم،وتبين ذلك من خلال نتائج اختبارchi-squareحيث أوضحت النتائج وجود علاقة ذات دلالة احصائية بين ملكية المسكن واعتبارها أحد خصائص البيئة السكنية التي ساعدت على رفع جودة حياة أفراد العينة في الضاحية،بينما لم تكن هناك علاقة ذات دلالة احصائية بين متغير الجنس واعتبار البيئة السكنية والبنية التحتية أثرت على جودة حياتهم حيث أن جميع أفراد العينة بغض النظر عن جنسهم يتمتعون بخصائص الضاحية،أما مؤشر المرافق الخدمية فتبين وجود علاقة ذات دلالة احصائية بينه وبين متغير العمر حيث أن الأفراد الأقل سناً يستفيدون من المرافق التعليمية والترفيهية لأبنائهم أكثر من كبار السن.وأوصت الدراسة بضرورة عمل الدراسات التي تقيس رضا الأفراد عن أحيائهم السكنية للتعرف على أهم المؤشرات التي تزيد من مستوى جودة حياتهم مما يساعد صانعي القرار في وضع الخطط التنموية الخاصة بالأحياء السكنية وفق أفضل المعايير التي تحقق أعلى مستويات الرضى لدى الأفراد.
Some thoughts about artificial stupidity and artificial dumbness
Authors: Lieber Jean , Mailly Jean-Guy , Marquis Pierre , Prade Henri , Rollin François
Published: December 2023

In a recently published book, the French writer and comedian François Rollin has discussed various aspects of the notion of stupidity, including artificial stupidity, the stupid counterpart of artificial intelligence. His claim is that a system of artificial stupidity is a system that provides wrong answers to any task it should solve, leading to absurd solutions in most cases. We believe that this claim is (at least partially) false and that designing artificial stupidity is not as trivial as it seems. In this article, we discuss why and how one could design a system of artificial stupidity. We believe that such a reflection on (artificial) stupidity can bring about some interesting insights about (artificial) intelligence.
Research on Rollover Threshold Value of Tank Truck
Authors: Xu Xiaodong , Deng Guide , Feng Heyi , Yang Zhirong , Liu Xin , Xu Yongsheng
Published: December 2023

The purpose of this paper is to provide reference for safety warning and accident recovery of tank truck rollover. The calculation method of critical lateral acceleration of tank truck considering liquid sloshing is studied by combining analytical method and multi-body dynamics simulation method. In this paper, three methods are presented to solve the critical lateral acceleration of tank truck rollover considering liquid sloshing, which are analytical method, step steer simulation method and tilt table simulation method respectively. The liquid sloshing is simplified to two-dimensional liquid sloshing by assuming that the lateral acceleration of the tank truck is constant. The change of liquid center of gravity is used to be equivalent to the effect of liquid sloshing on tank truck rollover. The influence data of liquid sloshing, tire, suspension system and tank truck center of gravity on the rollover of tank truck were obtained. The research results can be applied to the safety warning and accident recovery of tank truck.
Event-Triggered Delayed Impulsive Control for Stochastic Delayed Systems
Authors: Li Peng , Liu Linna , Li Zhao , Chai Xuzhao
Published: December 2023

In this paper, the stabilization issue is investigated for stochastic delay systems via event-triggered delayed impulsive control (ETDIC) strategy. For the system model, both the delay in stochastic differential equations and impulsive controller are taken into account. Based on the designed ETDIC, some sufficient conditions can be obtained for the mean-square exponential stability of stochastic delayed systems under the premise of non-Zeno phenomenon.
Research on Key Technologies of Intelligent Capture System for Personnel Position and Attitude
Authors: Li Hejia , Yao Zhao , Li Jiuchao , Lu Suo
Published: December 2023

This article addresses the issue of the lack of real-time monitoring of personnel’s position and posture information technology in special environments. Relying on intelligent capture systems, key technologies such as Beidou positioning, inertial navigation, network communication, 3D modeling, virtual simulation, etc. are utilized to achieve real-time restoration of personnel information, human posture data, motion status, and trajectory on situational maps in various environments. The entire process is collected and stored for command and decision-making provide technical support for comprehensive analysis.
Experimental and Application Analysis for Transfer Characteristic of Fluid Elastomer
Authors: Feng Zhizhuang , Qian Feng , Lu Xing , Dai Zhixiong , Yuan Xi
Published: December 2023

This paper takes the conventional fluidelastic isolator as the investigate subject, and the physical parameters affecting the optimal vibration isolation frequency and vibration displacement transfer rate are analyzed. Based on the simplified dynamic model and the performance test results of a fluidelastic isolator, the influence of fluid orifice damping, rubber stiffness, rubber loss coefficient, and coordination deformation relationships of the isolator were taking into consideration. A modified simulation analysis model has been obtained for the transmission characteristics of fluidelastic isolator. The vibration reduction test of the fluidelastic isolator was carried out, and the calculation results were verified. The results show that the simulation error of the modified fluidelastic isolator is smaller than that of the simplified model. It also shows good agreement between the influence of external excitation displacement on the transfer rate and the experimental results.
Analysis of the Influence of Blade Tip Geometry on the Aeroelastic Response of Rotors
Authors: Sun Fengnan , Zhu Yan , Lu Xing , Cheng Qiyou , Wang Siwen , Xing Longtao
Published: December 2023

Using the theory of moderately deformed beams and considering the nonlinear displacement coordination relationship at the blade tip, a differential equation of rotor aeroelasticity with different blade tip shapes was established. The aeroelastic responses of rotor blades with forward convex and backward swept, backward swept and backward reversed angles were systematically analyzed. The results showed that forward swept and backward swept were beneficial for rotor vibration reduction, while downward reversed caused significant fluctuations in response, and the amplitude changes of the blade tip were different at different reverse angles, this may have adverse effects on the vertical vibration response of the aircraft body. When using a lower angle to achieve noise reduction and improve rotor aerodynamic performance, the dynamic impact caused by the complexity of flow field motion should be considered to avoid excessive vibration.
Fuzzy Assessment of the Effectiveness of Innovative Projects in Industry
Authors: Mutovkina Nataliya
Published: December 2023

The innovative activity of industrial enterprises is the key to their successful operation and maintaining competitiveness in the market. The useful of innovations in product manufacturing technology, as well as in the management and control system, allows not only to maintain competitive positions but also to strengthen them. However, any innovative activity requires financial investments. Assessing the expediency of these investments, ensuring the possibility of comparing the planned results with the costs of innovation, is a problematic area of this work. Despite the certain development and proposals of solutions in this area, the problem of accurate assessment of the effectiveness of innovations remains relevant. This is important to the specifics of industrial enterprises, their industry affiliation, financial and other capabilities. As practice and set publications on this topic show, there is no single method for evaluating the effectiveness of innovations. The decision to invest in innovation is influenced by many factors that are different for each business entity. Most owners and managers, when evaluating innovative projects, solve the problem of choice, relying on traditional methods of calculating performance indicators and considering an innovative project as an investment. Such methods include calculations of net discounted income, internal rate of return, payback period of the project, profitability index, and other indicators. However, when using these methods, the qualitative effects of the introduction and application of innovations are not taken into account. In addition, the quantitative effects expected from the use of innovations are also predictive values evaluated by experts. Accordingly, there is always a possibility that these effects will not be obtained. Decision making on the investment of an innovative project becomes more complicated if we are talking about several projects. Then making a decision that reduces to a binary value (the project is accepted/the project is rejected) turns into a choice task. Such a problem is characterized by a larger dimension, therefore, an increased complexity of the solution. The more alternatives, the higher the difficulty (the harder the choice). The article proposes a method for fuzzy evaluation of the effectiveness of innovative projects in industry, which is based on the formation of a system of linguistic expert rules. This system is being developed based on the results of active work with experts in industrial innovation and represents a fuzzy knowledge base. As a criterion for the effectiveness of such a system, the level of consistency of the solutions proposed by the system with expert assessments of the effectiveness of an innovative project serves. If the system shows results that are practically indistinguishable from the results issued by the expert group, then a decision is made on its operation.
Estimating the Weitzman Overlapping Coefficient Using Integral Approximation Method in the Case of Normal Distributions
Authors: Eidous Omar M. , Al-Shourman Abeer J.
Published: December 2023

Given that we have two independent random samples, each of which follows a normal distribution, the main objective of this paper is to estimate the overlapping Weitzman coefficient . This coefficient is widely used and is defined as the area under two probability density functions. The proposed estimation technique is based on the rules of integral numerical approximation such as trapezoidal rules and Simpson’s rules. Simulation results showed the effectiveness of the proposed technique over some of the methods found in the literature.
Computer Modelling of Thermal Interaction in the Pile Foundation System of a Railway Bridge Support Structure in Permafrost
Authors: Filimonov Mikhail Yu. , Vaganova Nataliia A.
Published: December 2023

A new model and computer program have been developed to describe the propagation of non-stationary thermal fields in frozen soils with complex lithology for pile foundations of capital construction projects. The results obtained were used to predict changes in the dynamics of the bearing capacity of soil for the emergency support structure of a railway bridge in the permafrost zone. This support structure consists of 12 large-diameter piles, for which solar radiation is also considered for the piles located on the southern part of the support structure, which makes it possible to observe the effect of a thermal bridge, when during the summer season the accumulated heat spreads deeper and faster into the pile than through the ground due to higher thermal conductivity of the pile concrete. In the approach the prehistory of the thermal processes in the soil foundation is essential for the bearing capacity estimation. The results of numerical calculations are presented.
Power Terminal Detection System Based on Graph Neural Network
Authors: Deng Hongxin , Zhang Liang , Li Hangzhou , Wang Wei , Li Zheng
Published: December 2023

The power terminal detection system is an important part of the power system. It is of great significance to improve the intelligence of the power detection system to maintain the safety of the power system. However, the existing detection system relies more on traditional methods, which reduces the intelligence and accuracy of the detection system. Based on this, this paper proposes a power terminal detection method based on graph neural network. Firstly, the network flow data is used to model the power system as a node with no feature but sideband feature graph. Then, the graph neural network is used to iteratively learn the vector representation of each node in the communication topology according to the features of edges in the graph. Finally, nodes are classified according to the vector representation, so as to detect the vulnerabilities in the power system. When learning node representation, the proposed method considers the flow characteristics of power system and the communication topology of power system at the same time, and clearly considers the direction of edges in the graph. In addition, the proposed method is inductive, so it can adapt to the dynamic changes of power system. Experimental results on two public datasets show that the proposed method can converge quickly during training, and the Micro-F1 score of the proposed method is higher than that of the model that cannot use the power system communication topology information. Compared with other methods, the proposed method is easier to generalize to the unseen data during training.
Embedded Mechanical Engineering Controller Design Using LSTM Technology
Authors: Shi Lei , Wu Yongshun , Xia Zhaodan , Zhao Wei , Wang Haibo
Published: December 2023

Embedded controllers are very competitive in the market and can be seen worldwide in a wide range of applications from office automation equipment, consumer electronics, telecommunication, smart instrumentation to automotive electronics, financial electronics, industrial control and other different fields. The embedded construction machinery controller designed in this paper is mainly used in automotive electronics and construction machinery, and the design process mainly defines the functions of the controller according to the structural system of construction machinery and the functional module requirements of the control. In this paper, a fault time series prediction method based on long short-term memory (LSTM) recurrent neural network is proposed from the data, including network structure design, network training and prediction process implementation algorithm, etc. Further, with the goal of minimizing the prediction error, a multi-layer grid search-based LSTM prediction model parameter preference algorithm is proposed, and through experiments with a variety of typical time series prediction models The proposed LSTM prediction model and its parameter selection algorithm are verified to be highly applicable and accurate in the implementation of the embedded controller.
Performance Evaluation of a Maximum-Likelihood Optimum Receiver
Authors: Patra Trilochan , Mitra Swarup Kumar
Published: December 2023

This paper introduces the sequential intervention cancellation (SIC) detection method which is an encouraging method for increasing the efficacy regarding cellular networks with comparatively small additional complexity. This scheme renders much advantage as well as does not demand the exact orthogonal to be necessitated for time-space block encoding. Contiguous manifolding needs very robust decision process at the receiver. This paper focuses on one to five ordered sequential intervention cancellation (SIC) detection methods. SIC is adopted for diminishing interference. To achieve better performance, 2x2 MIMO and 4x4 MIMO techniques have been adopted in this paper. It uses flat Rayleigh damping of individual transmitter-receiver links for the non-coded BPSK, QPSK, 8PSK, 16PSK and 32PSK modulation systems. The details of ideal medium is determined at the acceptor without feedback to the sender. This paper presents a pair of non-linear intervention cancellation procedures like zero-forcing (ZF) as well as minimum-mean-square-error (MMSE) including symbol rejection and at the same time differentiates the performances with the maximum-likelihood (ML) optimum receiver.
Bilateral breast cancer and the influence of body mass index in clinicopathological features and overall survival
Authors: Luís Carla , Fernandes Rute , Dias João , Pereira Deolinda , Firmino-Machado João , Baylina Pilar , Fernandes Rúben , Soares Raquel
Published: December 2023

BACKGROUND: Breast cancer (BC) and obesity are two closely associated pathologies with increasing incidence and mortality rates. Bilateral Breast Cancer (BBC) displays a low incidence rate within BC and obesity represents a major risk factor. OBJECTIVE: The aim of this study is to analyzed BBC clinicopathological features distribution and determine the potential influence of obesity in BBC in these same features and overall survival. METHODS: Clinicopathological information was obtained from 42 cases of women with BBC diagnosed in IPO-Porto. To evaluate the frequency distribution of the clinicopathological data, a chi-square goodness of fit test was performed for BBC cases. A chi-square test of independence was applied for BMI stratification. Cox regression was performed for overall survival. Statistical significance was set at p-value < 0.05. RESULTS: Distribution of BBC clinicopathological features was found to be statistically significant in family history (p-value < 0.001), BBC type (p-value < 0.001), stage (p-value = 0.005), differentiation grade (p-value < 0.001), receptor expression (p-value < 0.001) and histological type (p-value = 0.031). In comparison to the statistical expected results, we observed an increased cases of absence of family history and less cases of metachronous BBC. Histological types between tumours of BBC were mostly concordant. All cases presented concordant receptor expression. Analysis stratified by BMI revealed that obese women were diagnosed later, although without statistical significance. All obese women presented poor differentiation grade (n = 6). Overweight patients display a tendency to a better overall survival with lower tumour stages and lower differentiation grades. CONCLUSIONS: Our results reveal the same receptor expression between contralateral tumours. Also, most tumours share the same histological type. When stratified by BMI, we observed a tendency for overweight women to have improved overall survival.
PARP Inhibitors for Metastatic Urothelial Carcinoma: A Systematic Review of Efficacy and Safety
Authors: Crabb Simon J. , Khalid Taha , Woods Lois , Frampton Geoff , Shepherd Jonathan
Published: December 2023

BACKGROUND:

Poly (ADP-ribose) polymerase (PARP) inhibitors have activity in various cancers. Metastatic urothelial carcinoma (MUC) is platinum sensitive and a subset harbour DNA repair gene alterations.

OBJECTIVE:

To assess evidence for efficacy and safety of PARP inhibition for MUC.

METHODS:

This systematic review included randomised clinical trials (RCTs) evaluating PARP inhibitors as monotherapy, or in therapeutic combinations, compared to relevant comparators or best supportive care. The primary endpoint was progression free survival (PFS). We searched MEDLINE (Ovid), EMBASE, ClinicalTrials.gov and Cochrane Central Register of Controlled Trials from March 2013 to March 2023. Each study was appraised using the Cochrane Risk of Bias 2 Tool. Study results were synthesised descriptively. Registration: PROSPERO CRD42023403145.

RESULTS:

From 247 identified reports, we included three phase 2 RCTs including 252 patients. Two RCTs assessed PARP inhibition in unselected patient groups (one first line platinum ineligible, one post chemotherapy maintenance) and found no evidence of efficacy. All three RCTs assessed subgroups defined by biomarker selection for somatic DNA repair defects. Two of these identified PFS benefit with PARP inhibition compared to a relevant comparator (one first line in combination with immunotherapy, one maintenance monotherapy). Safety outcomes were consistent with prior experience of PARP inhibitors. The risk of bias across the outcomes was generally low.

CONCLUSIONS:

PARP inhibitors lack efficacy for unselected MUC patients. Phase 2 RCTs support further investigation of PARP inhibition within biomarker-selected patient subsets. The optimal biomarker is not yet determined. Limitations in the current evidence relate to small sample sizes and low statistical power.
Changes in the pulmonary circulation due to gravitational loads in high altitude conditions
Authors: Absatirova Venera , Shandaulov Assylbek , Khamchiyev Kureysh , Shukurov Firuz , Khalimova Fariza
Published: December 2023

BACKGROUND:

The impact of gravity on the existence of all living things has long been of interest to scientists. The force of the Earth’s gravity combined with hypoxia significantly affects blood circulation and blood accumulation in various parts of the human and animal body. To date, the relationship between body position and blood circulation in pulmonary circulation under hypobaric hypoxia has not been sufficiently studied.

OBJECTIVES:

Therefore, the research aims to determine the possibility of changing the body position in space on the reactions in the pulmonary circulation in the plains and highlands.

METHODS:

For this purpose, research was conducted on male Wistar rats, 44 of whom spent 150 days at an altitude of 3200 m above sea level, and 25 representatives of the control group - at an altitude of 164 m.

RESULTS:

The study revealed that gravitational redistribution of blood in mountainous conditions is less pronounced compared to the control group. This is explained by the remodeling of the vascular wall and an increase in its stiffness. It was found that a change in pulmonary artery pressure at the time of a change in body position was recorded both on the plains and in the highlands. On the plains, when the body position of rats was changed to passive orthostatic, a decrease in systolic and diastolic pulmonary artery pressure was noted, and when the body position was changed to passive anti-orthostatic, an increase in pulmonary artery pressure was observed. The increase in pulmonary artery pressure was a compensatory mechanism due to the increased stiffness of the pulmonary vasculature.

CONCLUSIONS:

The practical significance of this research is to expand the understanding of the pathogenesis of pulmonary hypertension in high-altitude hypoxia.
OA usage reporting: Understanding stakeholder needs and advancing trust through shared infrastructure
Authors: Lloyd Tim , Miller Tricia , Drummond Christina , Kemp Jennifer
Published: December 2023

The complexity of usage reporting for Open Access (OA) content continues to grow, particularly with content syndication to organizations such as ScienceDirect and ResearchGate, which deliver content across multiple platforms at an unprecedented scale. What kind of usage data do diverse stakeholders (including libraries, publishers, authors, and editors) need? Can the work done to support OA book usage data analytics use cases inform OA article and data use cases? What standards and policies are required to ensure the usage data is accurate and meaningful? What infrastructure is needed to collect and disseminate this data effectively and efficiently?

This paper brings together four different perspectives to consider these questions: an OA publisher, a research infrastructure, an emerging usage data trust, and a usage analytics service provider. The authors walk through what is known, and then start to unpack the questions for which they do not yet have answers. Their goal is to inform the community’s understanding of the challenges ahead and, hopefully, start to lay the groundwork for constructive policies and shared solutions.
Dysregulation of Human Juvenile Huntington’s Disease Brain Proteomes in Cortex and Putamen Involves Mitochondrial and Neuropeptide Systems
Authors: Podvin Sonia , Mosier Charles , Poon William , Wei Enlin , Rossitto Leigh-Ana , Hook Vivian
Published: December 2023

Background: Huntington’s disease (HD) is a genetic neurodegenerative disease caused by trinucleotide repeat CAG expansions in the human HTT gene. Early onset juvenile HD (JHD) in children is the most severe form of the disease caused by high CAG repeat numbers of the HTT gene. Objective: To gain understanding of human HD mechanisms hypothesized to involve dysregulated proteomes of brain regions that regulate motor and cognitive functions, this study analyzed the proteomes of human JHD cortex and putamen brain regions compared to age-matched controls. Methods: JHD and age-matched control brain tissues were assessed for CAG repeat numbers of HTT by PCR. Human brain JHD brain cortex regions of BA4 and BA6 with the putamen region (n = 5) were analyzed by global proteomics, compared to age-matched controls (n = 7). Protein interaction pathways were assessed by gene ontology (GO), STRING-db, and KEGG bioinformatics. Results: JHD brain tissues were heterozygous for one mutant HTT allele containing 60 to 120 CAG repeats, and one normal HTT allele with 10 to 19 CAG repeats. Proteomics data for JHD brain regions showed dysregulated mitochondrial energy pathways and changes in synaptic systems including peptide neurotransmitters. JHD compared to control proteomes of cortex and putamen displayed (a) proteins present only in JHD, (b) proteins absent in JHD, and (c) proteins that were downregulated or upregulated. Conclusions: Human JHD brain cortex and putamen regions display significant dysregulation of proteomes representing deficits in mitochondrial and synaptic neurotransmission functions. These findings advance understanding of JHD brain molecular mechanisms associated with HD disabilities.
RETRACTED: The reptile optimized deep learning model for land cover classification of the uppal earth region in telangana state using satellite image fusion
Authors: Aruna Sri P. , Santhi V.
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Research on social ecological evaluation of the spatial form of old urban blocks based on dual probabilistic linguistic term sets
Authors: Li Wenjuan , Yi Xiduo
Published: December 2023

Under the rapid process of urbanization, many early renovated urban villages have also encountered many problems. Due to the rapid development of urban construction and the continuous changes in spatial functions, early renovated urban villages have already encountered problems such as unreasonable commercial distribution, lack of parking spaces, reduced commercial vitality, and commercial activities crowding out affecting the normal lives of villagers. There is a serious contradiction between the need for development and the quality of life of villagers. Due to the fixed nature of architectural space, only by fully understanding the essential morphological characteristics of the space can we find the optimal solutions for different space usage functions, and obtain the matching of the optimal solutions in the existing space requirements. The social ecological evaluation of the spatial form of old urban blocks is a multi-attribute group decision making (MAGDM). Recently, the grey relational analysis (GRA) and CRITIC method has been used to cope with MAGDM issues. The dual probabilistic linguistic term sets (DPLTSs) are used as a tool for characterizing uncertain information during the social ecological evaluation of the spatial form of old urban blocks. In this manuscript, the dual probabilistic linguistic GRA (DPL-GRA) method is built to solve the MAGDM under DPLTSs. The CRITIC method is used to obtain the attributes weights. In the end, a numerical case study for social ecological evaluation of the spatial form of old urban blocks is given to validate the proposed method.
Smart intrusion detection system with balanced data in IoMT infra
Authors: Umamaheswaran S. , Mannar Mannan J. , Karthick Raghunath K.M. , Dharmarajlu Santhi Muttipoll , Anuratha M.D.
Published: December 2023

The IoMT (Internet of Medical Things) has allowed for uninterrupted, critical patient observation, improved diagnosis precision, and efficient therapy. However, despite the usefulness of such medical things (devices), they also raise a lot of confidentiality and security issues since they provide potential entry points for hackers to exploit. Therefore, there is a pressing need for a technique for detecting network intrusions that combines precision, flexibility, and consistency. Addressing diverse information sources is challenging for finding negligible intrusions in sophisticated network systems, a core problem for current Intrusion Detection Systems (IDS). In this research, we propose a deep learning-based method for efficient network IDS in cases when data is unevenly distributed. Therefore, to address the poor identification rate of intrusions, we present a unique CGAN-CNN (Conditional Generative Adversarial Network-Convolutional Neural Network) IDS approach that oversamples from the unbalanced information based on the CGAN paradigm to overcome the functional deterioration induced by such unbalanced data, especially during intrusion detection. In addition, the sub-networks’ critic and generator each get additional constraints as part of the CGAN’s standard operating procedure, which helps to reduce the amount of leeway in the convergence process and speeds up the impact of convergence. To validate the effectiveness of the suggested model, we conducted an investigation using the most contemporary publicly available datasets, namely NIDS (Network Intrusion Detection System), and the CICDDoS2019 (Canadian Institute for Cybersecurity Distributed Denial of Service 2019) dataset from the Canadian Institution for Cybersecurity, and for healthcare-oriented image datasets Kaggle, respectively. The experimental findings validated the superiority of the CGAN-CNN approach described in this research. Notified as more trustworthy indications, F1-score and precision performed at 97.88%, and 97.15%, respectively.
RETRACTED: Constraint-based high utility mobile trajectory pattern mining for security systems
Authors: Li Aiguo , Feng Rongrong
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
RETRACTED: Deep reinforcement learning for QoS-driven cloud healthcare services selection: A framework and performance evaluation
Authors: Wang Ling , Ni Zhiyun
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
A novel outlier calendrical heterogeneity reconstruction deep learning model for electricity demand forecasting
Authors: Songhua Huan
Published: December 2023

The development of an accurate electricity demand forecasting model is of paramount importance for promoting global energy efficiency and sustainability. Nonetheless, the presence of outliers and inappropriate model training can result in suboptimal performance. To tackle these challenges, this study explores the potential of Convolutional Neural Network (CNN) and active learning theory as forecasting solutions, offering high efficiency and advantages for long time series. In this study, a hybrid model that combines Isolation Forest (IF), Outlier Reconstruction (OR), CNN and Random Forest (RF) is conducted to mitigate computational complexity and enhance the accuracy of electricity demand forecasting in the presence of outliers. IF is employed to detect outliers in electricity demand time series, while OR is used to reconstruct subsequences based on calendrical heterogeneity for training. CNN is applied for both training and forecasting, and the final output is combined using RF. The effectiveness of the proposed IF-OR-CNN-RF model is validated using electricity data collected from recent sources in Australia at different sampling frequency. The experimental results demonstrate that, in comparison with other popular CNN-based electricity demand forecasting models, IF-OR-CNN-RF model outperforms with significantly improved performance metrics. Specifically, Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and R-squared values are 77.92, 179.18 and 0.9769 in 5-minute frequency; 162.67, 353.96 and 0.9775 in 10-minute frequency; 841.27, 1374.79 and 0.9622 in 30-minute frequency; 2746.01, 3824.00 and 0.9262 in 60-minute frequency; 9106.08, 12269.04 and 0.8044 in 120-minute frequency. IF-OR-CNN-RF model represents a valuable framework for future electricity demand forecasting, particularly in scenarios involving outliers.
The West of Scotland Cohort of Mitochondrial Individuals with the m.3243A>G Variant: Variations in Phenotypes and Predictors of Disease Severity
Authors: Saunders Charlie , Longman Cheryl , Gorman Grainne , James Kelly , Oliwa Agata , Petty Richard , Snadden Lesley , Farrugia Maria Elena
Published: December 2023

Background:

The m.3243A>G variant is the commonest mitochondrial (mt) DNA pathogenic variant and a frequent cause of mitochondrial disease. Individuals present with a variety of clinical manifestations from diabetes to neurological events resembling strokes. Due to this, patients are commonly cared for by a multidisciplinary team.

Objectives:

This project aimed to identify patients with confirmed mt.3243A>G-related mitochondrial disease attending the Muscle Clinic at Queen Elizabeth University Hospital in Glasgow. We explored potential correlates between clinical phenotypes and mtDNA heteroplasmy levels, HbA1c levels, body mass index, and specific clinical manifestations. We investigated if there were discrepancies between non-neurological speciality labelling in clinical records and individuals’ phenotypes.

Methods:

Data were gathered from the West of Scotland electronic records. Phenotypes were ascertained by a clinician with expertise in mitochondrial disorders. Statistical analyses were applied to study relationships between tissue heteroplasmy, HbA1c and clinical phenotypes including body mass index (BMI).

Results:

Forty-six individuals were identified from 31 unrelated pedigrees. Maternally inherited diabetes and deafness was the prominent syndromic phenotype (48%). A significant association was found between overall number of symptoms and bowel dysmotility ( p < 0.01). HbA1c was investigated as a predictor of severity with potential association seen. Although used widely as a prognosticator, neither corrected blood nor urine mtDNA heteroplasmy levels were associated with increased number of symptoms. In 74.1% of records, syndromic phenotypes were incorrectly used by non-neurological specialities.

Conclusions:

This m.3243 A > G patient cohort present with marked clinical heterogeneity. Urine and blood heteroplasmy levels are not reliable predictors of disease severity. HbA1c may be a novel predictor of disease severity with further research required to investigate this association. We infer that prognosis may be worse in patients with low BMIs and in those with bowel dysmotility. These results underscore a multidisciplinary approach and highlight a problem with inaccurate use of the existing nomenclature.
Folic acid prescription practice for high-risk prevention of spina bifida at a tertiary care hospital in Addis Ababa, Ethiopia
Authors: Yesehak Bethelehem , Dorsey Amanda , Zewdie Kibruyisfaw , Kancherla Vijaya , Ashagre Yordanos
Published: December 2023

PURPOSE: Mothers who have had a pregnancy affected by spina bifida are advised to take 4-5 mg/day folic acid pills to prevent recurrence. The folic acid prescription pattern was examined for high-risk mothers whose children received spina bifida surgery in an urban Ethiopian hospital. METHODS: Data were analyzed from a large Ethiopian urban tertiary care hospital that provided spina bifida care. General practitioners recorded 5 mg/day folic acid prescriptions administered to mothers of infants with spina bifida born between January 2019 and June 2022. RESULTS: Among 500 baby-mother pairs, 340 (68%) received a 120-day prescription for 5 mg/day folic acid pills. Of these 340 mothers, 331 (97%) received their folic acid prescription at their child’s first or second patient encounter. Almost all mothers (94%) had documentation of only one prescription for the study duration. The percentage of mothers receiving at least one prescription varied by the baby’s year of birth (2019:75%; 2020:92%; 2021:46%; Jan 2022 –June 2022:79%). CONCLUSION: This prioritization of spina bifida recurrence prevention demonstrates feasibility for other healthcare centers in low-income countries. Sustained funds to provide women with free folic acid pills can favor high compliance and uptake of this prevention intervention.
Some systemic risk indicators
Authors: El Qalli Yassine , Said Khalil
Published: December 2023

This paper aims to introduce novel systemic risk indicators based on risk allocation methods employed in actuarial science. We present diverse general approaches for constructing these indicators and utilize them to derive indicators based on commonly used risk measures such as Value at Risk, Tail Value at Risk, and Expectiles. Furthermore, we analyze the influence of the dependence structure on the behavior of these indicators using a range of copula models. To support our findings, we provide numerical illustrations.
NeuSyRE: Neuro-symbolic visual understanding and reasoning framework based on scene graph enrichment
Authors: Khan M. Jaleed , G. Breslin John , Curry Edward
Published: December 2023

Exploring the potential of neuro-symbolic hybrid approaches offers promising avenues for seamless high-level understanding and reasoning about visual scenes. Scene Graph Generation (SGG) is a symbolic image representation approach based on deep neural networks (DNN) that involves predicting objects, their attributes, and pairwise visual relationships in images to create scene graphs, which are utilized in downstream visual reasoning. The crowdsourced training datasets used in SGG are highly imbalanced, which results in biased SGG results. The vast number of possible triplets makes it challenging to collect sufficient training samples for every visual concept or relationship. To address these challenges, we propose augmenting the typical data-driven SGG approach with common sense knowledge to enhance the expressiveness and autonomy of visual understanding and reasoning. We present a loosely-coupled neuro-symbolic visual understanding and reasoning framework that employs a DNN-based pipeline for object detection and multi-modal pairwise relationship prediction for scene graph generation and leverages common sense knowledge in heterogenous knowledge graphs to enrich scene graphs for improved downstream reasoning. A comprehensive evaluation is performed on multiple standard datasets, including Visual Genome and Microsoft COCO, in which the proposed approach outperformed the state-of-the-art SGG methods in terms of relationship recall scores, i.e. Recall@K and mean Recall@K, as well as the state-of-the-art scene graph-based image captioning methods in terms of SPICE and CIDEr scores with comparable BLEU, ROGUE and METEOR scores. As a result of enrichment, the qualitative results showed improved expressiveness of scene graphs, resulting in more intuitive and meaningful caption generation using scene graphs. Our results validate the effectiveness of enriching scene graphs with common sense knowledge using heterogeneous knowledge graphs. This work provides a baseline for future research in knowledge-enhanced visual understanding and reasoning. The source code is available at https://github.com/jaleedkhan/neusire.
Impact of the University of Namibia merger on staff and students
Authors: Lopez Razavi O. , Mbodo L.
Published: December 2023

The merger of the University of Namibia (UNAM) with the four Colleges of Education in 2010 was necessitated by an Act of Parliament for tertiary institutions. This study aims to identify the challenges for staff and students to cope with the merger, in order to bring the merger process to the attention of the stakeholders. This study is important because, while history is being made, one needs to establish the human experiences of those going through these changes. It is intended to capture the merger’s impact on the academic, administrative and auxiliary staff and students. Participants responded to open-ended questionnaires and interviews designed to assess their perceptions of capabilities in their new roles, as well as the responsibilities, constraints and opportunities availed for personal and professional growth. The students who participated are the former BETD (Basic Education Teacher Diploma) students who were articulated into the B.Ed. (Bachelor of Education) Lower and Upper Primary program during the merge. Preliminary results indicated that the majority of the participants had positive experiences after joining UNAM. Challenges in the following areas were highlighted: infra-structure, unreliable communication technologies, the breadth and depth of work covered in some modules, diminishing philosophy of learner-centered education. A few participants voiced their concerns regarding some anomalies. A number of suggestions from the different stakeholders to make the merger even more effective and efficient are offered.
High school teachers perceptions on reflective practice in teaching at one selected school in Khomas region, Namibia
Authors: Villet Charmaine B. , Kapenda Hileni M. , Simasiku Enock L.
Published: December 2023

This paper presents a case study of high school teachers’ perceptions on reflective practice in teaching at one selected school in the Khomas region. A qualitative approach was used in this study and fourteen teachers were purposefully selected to participate in the study. Three types of data tools were used to gather information, namely; the lesson observation schedule, the interview schedule and an open-ended questionnaire. The data from the questionnaire was thematically analysed. The views of the teachers on reflective practice were transcribed, analysed, and presented in the descriptive form and the data from classroom observations? The findings revealed that most teachers at the selected school were familiar with the concept of reflective practice and they used reflective journaling and reflective supervision. Based on the study findings, it can be concluded that the teachers had different views on reflective practice in teaching. The majority indicated that reflective practice is a crucial component of teaching and learning and should be incorporated in daily teaching, while few teachers were of the opinion that reflective practice takes time away from valuable teaching time and as such, it should not be a component of the teaching process. It is recommended that further studies are needed to get a broader view of teachers’ perceptions in Namibia on reflective practice.
evolution of management theories
Authors: Tafirenyika Joice , Mandizvidza Christopher
Published: December 2023

This paper examines critically the evolution of management theories and how they have informed the supervisory practices of the Early Childhood Development (ECD) Programme in Zimbabwe. The paper identifies a number of management theories that have influenced the supervision of the ECD Programme in Zimbabwe. Theories that have been found to have greatly informed the supervision of the ECD Programme in Zimbabwe include Scientific Management, Systems and Contingency. However, the Bureaucratic Management, Administrative, Human Relations, Total Quality Management, Learning Organisation and Re-engineering theories have had some influence on the supervision of the ECD Programme. The paper was a desk review. Unlike others, the study established that the Quantitative Theory of Management was not as influential in the supervision of ECD because of the view held by most supervisors that managerial decisions and the nature of the ECD Programme itself cannot be quantified. The paper concludes that supervisory practices at any given point in time are indicative of the influences of the management thought prevalent during such a period and the human element in place. An important issue that emerged is that, even when and where new theories tend to be more pervasive, the influences of the already existing ones remain visible and influential to some extent.
ЕФЕКТИВНІСТЬ ЕКОНОМІКО-МАТЕМАТИЧНОГО МОДЕЛЮВАННЯ В ОПТИМІЗАЦІЇ БІЗНЕС-ПРОЦЕСІВ
Authors: Скорук Олена
Published: December 2023

У статті досліджено специфіку ефективності економіко-математичного моделювання в контексті оптимізації бізнес-процесів сучасних підприємств. Розглянуто різні аспекти та виміри моделювання та проаналізовано його потенціал для вдосконалення стратегій прийняття рішень та оптимізації ресурсного використання. Визначено теоретичні засади економіко-математичного моделювання та його ключові виміри, такі як прогнозування, аналіз ризиків та оптимізація ресурсів. Запропоновано підходи щодо практичного застосування економічних моделей у підвищенні ефективності бізнес-процесів. Розглянуто сучасні виклики та перспективи стосовно впровадження економіко-математичних моделей в сучасному бізнес-середовищі, враховуючи специфіку науково-технічного прогресу та суттєвого зростання потоків даних, котрі підлягають аналітичному опрацюванню. Запропоновано рекомендації щодо оптимального використання економіко-математичного моделювання для досягнення конкурентних переваг та стійкого розвитку підприємств. Доведено важливість інтеграції економіко-математичних моделей в стратегічне управління для забезпечення успішного досягнення цілей розвитку суб’єкта господарювання.