Effectiveness of Family Therapy in Social Work Practice in Buhara Sub-County Kabale District. by Tukamushaba, Vian

“…Establishing rapport and building a therapeutic alliance with each family member, some respondents also showed that creating a genogram to visually represents the family structure, relationships, and patterns across generations. …”
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Heat shock proteins gene family: Genome-wide identification in Micropterus salmoides and expression analysis under high-temperature stress by Meng Zhang, Shangjin Qiu, Yikai Li, Tianxi Fu, Jinhui Yu, Ke Ma, Yongtao Tang, Chuanjiang Zhou

“…The results revealed that although the 4 genes exhibited different expression patterns in different tissues, the genes were similar in terms of the overall expression pattern. …”
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Larval source management in Ethiopia: modelling to assess its effectiveness in curbing malaria surge in dire Dawa and Batu Towns by Galana Mamo Ayana, Abdollah Jalilian, Temesgen Ashine, Eshetu Molla, Elifaged Hailemeskel, Dagmawi Hailu Yemane, Hailegiorgis Yirgu, Nigatu Negash, Natnael Teferi, Daniel Teshome, Alison M. Reynolds, David Weetman, Anne L. Wilson, Birhanu Kenate, Martin J. Donnelly, Luigi Sedda, Endalamaw Gadisa

“…Weekly malaria passive case data were used to evaluate the change in the estimated malaria incidence rate and trends of temporal patterns of the estimated malaria incidence rate before and after interventions. …”
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Imputasi Data Temperatur Maksimum Menggunakan Metode Support Vector Regression by Isa Kholifatus Sukhna, Brina Miftahurrohmah, Catur Wulandari, Putri Amelia

“…Model evaluation employs the metrics Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R²), presenting the evaluation results with low error. …”
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A Review of Multidisciplinary Evidence on the Role of Urban Green Space in Improving the Sleep Quality of the Elderly by Ning KANG, Han XIE, Tao JIANG

“…Genetically, polymorphisms in circadian rhythm genes influence sleep patterns of the elderly. Regarding the microbiome, the gut-brain axis plays a crucial role. …”
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Science of science by S. Fortunato, C. T. Bergstrom, K. Börner, J. A. Evans, D. Helbing, S. Milojević, A. M. Petersen, F. Radicchi, R. Sinatra, B. Uzzi, A. Vespignani, L. Waltman, D. Wang, A.-L. Barabási

“…Those willing to break this pattern engage in riskier careers but become more likely to make major breakthroughs. …”
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Lateral Percolation and Its Effect on Shale Gas Accumulation on the Basis of Complex Tectonic Background by Kun Zhang, Zhenxue Jiang, Xuelian Xie, Zhiye Gao, Tianlin Liu, Lishi Yin, Chengzao Jia, Yan Song, Chang’an Shan, Yinghui Wu, Pengfei Wang

“…The above accumulation pattern was proved in several Areas. Also, this research presented a basis of evaluation units division. …”
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Census and Analysis of Higher-Order Interactions in Real-World Hypergraphs by Xihang Meng, Xuemeng Zhai, Gaolei Fei, Sheng Wen, Guangmin Hu

“…To address this issue, we introduce a new category of structural patterns, hypermotifs, which are defined as statistically significant local structures formed by interconnected hyperedges. …”
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Assessing GFDL‐ESM4.1 Climate Responses to a Stratospheric Aerosol Injection Strategy Intended to Avoid Overshoot 2.0°C Warming by Shipeng Zhang, Vaishali Naik, David Paynter, Simone Tilmes, Jasmin John

“…Furthermore, our analysis reveals that spatially heterogeneous forcing within the SAI scenario results in diverse climate feedback parameters in the GFDL‐ESM4.1 model, through varying surface warming/cooling patterns. This research highlights the importance of considering model structural uncertainties and forcing spatial patterns for a comprehensive evaluation of future scenarios and geoengineering strategies.…”
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Quantifying degradation in animal acoustic signals with the R package baRulho by Marcelo Araya‐Salas, Erin E. Grabarczyk, Marcos Quiroz‐Oliva, Adrián García‐Rodríguez, Alejandro Rico‐Guevara

“…We highlight the package features with a case study testing the effects of habitat and acoustic structure on signal propagation, two common factors evaluated in such experiments. …”
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The Deformation, Failure Mechanisms, and Stability Control of the Surrounding Rock of Deep Cross-Measure Roadway: A Case Study by Wenzheng Du, Rui Pan, Hongjin Sun

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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…Specifically, DGRL first integrates dimension reduction into ridge regression rather than treated them as two irrelevant steps, which enables us to capture the underlying subspace structure and correlation patterns among classes. Additionally, a graph regularizer that fully utilizes the local class information is developed and introduced to the new framework so as to enhance the classification accuracy and prevent overfitting. …”
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Microclimatic Divergence in a Mediterranean Canyon Affects Richness, Composition, and Body Size in Saproxylic Beetle Assemblages. by Jörn Buse, Samuel Fassbender, Martin H Entling, Tomas Pavlicek

“…We tested specific hypotheses of species richness patterns, assemblage structure, and body size resulting from interslope differences in microclimate. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…It involves transmitting electromagnetic signals into the ground and analyzing their responses to determine the geological structure, lithology, and fluid content of the formation. …”
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Integration of Artificial Neural Network Regression and Principal Component Analysis for Indoor Visible Light Positioning by Negasa Berhanu Fite, Getachew Mamo Wegari, Heidi Steendam

“…Experimental results show significant improvements across multiple evaluation metrics for a constellation comprising eight LEDs mounted in a rectangular structure measuring a room dimension of 12 m × 18 m × 6.8 m, with a photodiode (PD) receiver. …”
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Stability of Fluid Flow through a Channel with Flexible Walls by Marianna A. Shubov, Madeline M. Edwards

“…The main findings of the paper are the following: (i) rigorous formulation of the initial boundary problem for the stream function, ψx,y,t, induced by the fluid-structure interaction model, which takes into account the axisymmetric pattern of the flow and “no-slip” condition near the channel walls; (ii) application of a double integral transformation (the Fourier transformation and Laplace transformation) to both the equation and boundary and initial conditions, which reduces the original partial differential equation to a parameter-dependent ordinary differential equation; (iii) derivation of the explicit formula for the Fourier transform of the stream function, ψ˜k,y,t; (iv) evaluation of the inverse Fourier transform of ψ˜k,y,t and proving that reconstruction of ψx,y,t can be obtained through a limiting process in the complex k-plane, which allows us to use the Residue theorem and represent the solution in the form of an infinite series of residues. …”
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Analysis of deformation rule of deep foundation pit excavation of railway station in soft soil with silt by Weijian Liu, Zhonghe Wang, Zhizeng Zhang, Zhengyu Zhang, Yongfu Jia, Zhun Li

“…By analyzing actual monitoring data collected from the site, the study identifies patterns in the settlement and deformation of both the retaining structure and the surface. …”
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Research Progress on Information Model of Urban Green Space by Wei ZHANG, Yahan YAN

“…In terms of assessment and analysis, given the increasingly complex development trends of urban fabric, traditional two-dimensional assessment methods cannot meet the needs of complex green space evaluation. By establishing evaluation methods, green space information models can be applied to different practical needs: Calculation of three-dimensional green volume indicators, analysis of three-dimensional landscape patterns, and evaluation of three-dimensional spatial ecosystem services.ConclusionBased on the requirements for green space information modeling, a corresponding construction framework can be established, including data acquisition, composition structure, detail level, spatial scale, sharing platform and analysis application of green space information models. …”
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Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models by Benedictor Alexander Nguchu, Benedictor Alexander Nguchu, Yifei Han, Yanming Wang, Peter Shaw

“…We use machine learning (ML) algorithms, including Random Forest, Logistic Regression, and Support Vector Machine, to evaluate the diagnostic power of the brain features and network patterns in differentiating the PD subtypes and distinguishing PD from HC. …”
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Quantification and histochemical localization of secondary metabolites during development in Annona muricata L. (Annonaceae) by Aditi Venkatesh Naik, Krishnan Sellappan

“…As a result of high variability of metabolite production in A. muricata, the present study evaluated the histochemical analysis of various plant parts at different developmental stages of growth. …”
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