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  SpliceLoc-ML: A Location-Stratified Machine Learning Model for Non-Canonical Splice Variant Pathogenicity Prediction and Classification, with Application to Long QT Syndrome

  (2026-06) Wedad Jawdi Yaqoub Murrar; Dr. Yaqoub Ashhab

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  Non-canonical splice variants that occur outside the ±1/±2 GT-AG canonical splice site positions, represent a clinically important but computationally neglected class of genomic variation. Although splicing-disrupting variants account for approximately one-third of all disease-causing variants, the ACMG/AMP classification framework offers only weak computational evidence criteria for this class. Consequently, a large portion of pathogenic variants in these regions are excluded completely from analysis pipelines or in some cases classified as VUS, leaving patients undiagnosed despite carrying a disease-causing mutation that could be identified. To address this gap, this study develops SpliceLoc-ML, a location-stratified ensemble meta-classifier that predicts the pathogenicity of non-canonical splice variants and maps its output directly onto the ACMG/AMP five-tier classification. Three separate Random Forest models were trained, for exonic, near-splice (3–20 bp), and deep intronic (>20 bp) variants on 27,994 variants: 6,828 experimentally validated pathogenic variants from SpliceVarDB and 21,166 benign controls from gnomAD v4.1, integrating scores from SpliceAI, Pangolin, MaxEntScan, and CADD-PHRED with the GC content and polypyrimidine tract density. Thresholds were anchored to the Tavtigian Bayesian posterior probability framework with the lower VUS boundary derived from the training data using Youden's J statistic. All three models exceeded pre-defined performance thresholds, with AUROC values of 0.969, 0.975, and 0.936 and MCC values of 0.837, 0.853, and 0.811 for exonic, near-splice, and deep intronic variants respectively, outperforming every individual tool evaluated. SpliceLoc-ML was then applied to 4,349 non-canonical splice variants from Long QT Syndrome genes. The number of VUS decreased by 56.6% (from 489 in ClinVar to 212), and the model placed 54 variants in the Likely Pathogenic or Pathogenic tiers. These are computational assignments and need functional and clinical confirmation. These results establish SpliceLoc-ML as a reliable framework that connects computational splice variant prediction directly to clinical variant reporting.

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  Chronological Evolution of Living Space in Palestinian Residential Units: Assessing Spatial Configuration, Social Dynamics, and Thermal Performance

  (2026-08) Bara Awad Ahmad Obayat; Dr. Bader Alatawneh

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  Palestinian residential architecture has changed substantially across the Ottoman, Jordanian, and contemporary periods, with traditional spatial elements such as the courtyard and mastaba (raised Platform) giving way to newer forms like the liwan (enclosed central hall) and enclosed kitchen. These shifts, driven by political, social, and constructional change, have tended to be documented descriptively, with little attempt to connect them to measurable thermal performance. This study addresses that gap by tracing how spatial configuration across the three periods has shaped indoor thermal comfort, and by testing whether design strategies drawn from historical precedent can improve contemporary housing performance. Across the three periods, changes occurred in wall composition, window-to-wall ratios, and the relationship between interior spaces and the outside. Three case studies in Abu Dis were selected and verified against the study's case-selection criteria using a household questionnaire, then assessed through field measurements of indoor air temperature and relative humidity (one week in summer, 30 hours in winter) used to build and calibrate DesignBuilder/EnergyPlus models against ASHRAE Guideline 14. The Ottoman house showed a summer diurnal swing of just 1.8°C, against 4.4°C in the contemporary case, which fell outside the Fanger comfort range for 69.5% of summer hours. In the Jordanian case, parametric testing of window-to-wall ratio identified an optimal range of 18.5–30.9%; the contemporary case showed no single best ratio, with a summer/winter trade-off between the tested configurations instead. Reintroducing the veranda as a thermal buffer, tested on the Jordanian and contemporary cases only cut solar heat gain by 43.9% in summer and 66.3% in winter in the contemporary case, and lowered summer Predicted Percentage of Dissatisfied to 19.2% in the Jordanian case. Overall, Selective reuse of historical elements, such as optimized window-to-wall ratios and verandas, can improve passive thermal comfort in contemporary Palestinian housing by drawing on proven local building strategies.

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  Forensic Structural Assessment and Rehabilitation of an Existing Steel Truss Industrial Building: A Case Study

  (2026-05) Mohammed Ahmed ALBASHA; Dr. Belal Almassri

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  Steel truss systems are not only the most enduring but also the most adaptable structural systems that have been widely used in various application areas like industrial buildings, warehouses, storage buildings, and factories due to their high strength, large load carrying capacity and easy combining in an architectural and structural design manner. However, the adaptability of these structures to varying functional requirements has made it the major reason for their selection in the industrial and commercial sectors. Steel structures, despite being strong, are subjected to a range of environmental and structural deteriorations among which corrosion due to moisture and pollution is the most notorious, followed by buckling under heavy or unbalanced loads, connection failures caused by overload or poor execution quality, and their susceptibility to extreme weather, fire, and impacts. All these factors combined ultimately result in a decrease in the performance of the structure and hence the possibility of the public and property being at risk so the evaluation of the present condition and consequent rehabilitation becomes of utmost importance. This research will lead to the formulation of a comprehensive methodology for assessing the structural condition, analyzing the critical members, and designing an effective rehabilitation plan that will restore the structural performance to optimal levels and prolong the life of the building. It includes the application of field inspections, non-destructive testing, structural analysis, and establishment of rehabilitation techniques such as strengthening the already weakened members, replacement of the damaged building blocks, and Upgrading the connections and the structural supports. The objective of this study was to take an existing industrial building with a steel truss system and produce a full case study of it. The process will include first documenting the present status and carrying out a thorough inspection of the problematic members, then continuing with the structural analysis using advanced numerical finite element modeling in STAAD.Pro to evaluate the building's baseline capacity under extreme wind, seismic, and historic snow-load drifting scenarios. The research culminates in a targeted structural recovery plan, offering a multi-criteria engineering and economic evaluation between innovative in-situ retrofitting techniques and full structural replacement to restore global frame stability and guarantee lifecycle safety.

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  An Integrated Machine Learning and GIS Approach for Optimizing Hydrological SCS-CN Parameters and Runoff Prediction in the West Bank

  (2026-09) Rafiq Mazen Fareed Al-Rajabi; Dr Mutaz Qafisheh

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  Estimating runoff is a practical necessity in semi-arid regions, where a single intense storm can cause flooding in a season that is otherwise short of water. This study looks at the West Bank, where sparse gauging makes rainfall-runoff modelling difficult, and combines the SCS-CN method, GIS and machine learning to get more reliable runoff estimates. We processed rainfall records from 41 stations covering 2020–2024 and used them to build a hydrological database of nine variables, the most important being maximum precipitation (Pmax) and the curve number (CN). Before trusting the data-driven results, we calibrated a HEC-HMS model against observed discharge from the Alexander Basin. Adjusting CN for antecedent moisture condition (AMC) was what allowed the simulated peak discharge to match the observed one. Six machine learning models were then compared: Support Vector Regression (SVR), Random Forest, XGBoost, K-Nearest Neighbours (KNN), Decision Tree and Linear Regression. SVR came out on top with R² = 0.981 and an RMSE of 0.79 mm. Random Forest was second (R² = 0.974), followed by XGBoost (R² = 0.958). Across the models, Pmax turned out to be the strongest driver of surface runoff. These results suggest that machine learning can be a dependable tool for estimating runoff in ungauged basins, and the same approach could be applied to other semi-arid regions for flood risk assessment and water resource management.

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  Structural and Seismic Behavior of RC Buildings Retrofitted with External Wall Jacketing Due to Vertical Extension.

  (2026-05) Ahmed Khalil Khamis; Dr. Maher Amro

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  Urban areas face a continuously growing demand for residential and commercial spaces, driving the need for spatial optimization. Consequently the vertical extension of existing structures becomes an economically viable, and also sustainable, approach. In this study This study investigates the structural evaluation and seismic rehabilitation of an existing four-story reinforced concrete, RC, building which is planned to receive three additional floors, so it turns into a seven-story system. Because the new configuration comes with a major rise in static gravity loads and also in dynamic lateral seismic forces, an integrated retrofitting strategy is worked out. The strategy mainly leans on reinforced concrete, RC, jacketing on the external walls, to substantially increase the building’s lateral stiffness and its seismic resistance, at least in a practical sense. Advanced 3D structural finite element models of the building, in both its existing and its extended variants, were developed using ETABS in strict compliance with ASCE 7-16 and ACI 318-19 provisions. The analytical approach utilizes a code-compliant Equivalent Static and Dynamic Response Spectrum Analysis, incorporating effective cracked section stiffness modifiers to account for material aging and cracking in the legacy frame. The evaluation follows a systematic step-by-step review across the structural components. The work follows a rather strict, step by step review and design procedure across the structural components, without skipping too much. It starts with the foundation stage, where soil bearing strength is checked and the footing enlargement is detailed to carry the added gravity and overturning effects. After that, the internal columns that face higher axial forces are examined and then retrofitted, together with the installation of external shear wall jacketing. Here the main emphasis is on how well the shear is transferred between the older and newer concrete interfaces. Toward the end, the existing floor slabs are checked for both modified bending demands and potential punching shear failures. The results of this thesis give a kind of broad template for forensic, and rehabilitation engineers. In particular it provides useful perspectives on how to handle stiffness distribution, and how to reduce torsional seismic effects that can show up when external wall retrofitting is applied in vertically expanded structures.

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