Interpretation of the t.test in R

I got two distribution which are not pairs. It's difficult to say that they are also from a normal distribution because they have different length.

The distributions of the vectors are, for gas:

65  65  65  65  74  74  74  74  74  77  78  81  81  83  83  83  85  85  85  85  85  87  87
89  89  90  91  91  91  91  91  91  94  94  94  95  95  95  95  98 101 101 101 102 102 102
102 102 103 103 103 103 103 104 104 104 104 104 104 106 106 106 106 107 108 108 110 110 113
113 115 115 115 118 118 118 118 119 119 121 122 122 122 125 125 125 128 128 128 128 128 129
129 134 134 134 134 134 134 137 137 137 142 145 145 148 148 148 148 150 150 150 150 150 150
150 153 153 154 154 154 158 158 161 161 161 161 161 161 161 161 164 164 168 168 168 168 168
186 188 188 192 192 194 194 197 197 231 256

while for the diesel vector distribution is:

65  91  91  93  93  93  93  94  94  95 122 128 161 161 161

I made the t.test and the wilcox.test and I got these results:

Welch Two Sample t-test

data:  diesel_type and gas_type
t = -1.7104, df = 18.149, p-value = 0.1042
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -31.873874   3.256425
sample estimates:
mean of x mean of y 
109.0000  123.3087 

and Wilcoxon rank sum test with continuity correction

data:  diesel_type and gas_type
W = 843, p-value = 0.1179
alternative hypothesis: true location shift is not equal to 0

I could accept the null hypothesis in the t.test, saying that the means are equals because the p-value is over the 5%. Should I accept the null hypothesis in the Wilcoxon test too? Are the medians equals? What could I say about these results?