Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|     | A   | B                                                                                                                                                       | C                 | D   | E   | F   | G   | H   | I   | J   | K             | L   | M   | N   | O   | P   | Q   | R   | S   |
|----:|:----|:--------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------|:----|:----|:----|:----|:----|:----|:----|:--------------|:----|:----|:----|:----|:----|:----|:----|:----|
| 100 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 101 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 102 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 103 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 104 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 105 |     |                                                                                                                                                         | 1.173681403508772 |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 106 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 107 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 108 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 109 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 110 |     | To keep operation within the inductive region with an overload-current capability of 110%, Mg_max is increased from 1.17 to 1.17 × 110%                 |                   |     |     |     |     |     |     |     | [Target Cell] |     |     |     |     |     |     |     |     |
| 111 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 112 |     | Step 3: Select Ln and Qe                                                                                                                                |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 113 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 114 |     | From below figure, if the values Ln = 3.5 and Qe = 0.45 are selected, the corresponding Mg _ap = 1.56, which is greater than Mg_max = 1.29. A curve for |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 115 |     | Ln = 3.5 is not shown in Fig. but it can be obtained by interpolating the curves of Ln = 3 and Ln = 4.                                                  |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 116 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 117 |     | Ln                                                                                                                                                      | 3.5               |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 118 |     | Qe                                                                                                                                                      | 0.45              |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 119 |     |                                                                                                                                                         |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |
| 120 |     | Step 4: Determine the Equivalent Load Resistance (Re )                                                                                                  |                   |     |     |     |     |     |     |     |               |     |     |     |     |     |     |     |     |



min_row: 100
max_row: 120
min_col: 1
max_col: 19
target_cell_row_idx: 110
target_cell_col_idx: 11
target_cell_value: 1.287
formula: =1.17*110%