diff --git a/src/elisa/plot/scale.py b/src/elisa/plot/scale.py
index 616d0d62..883d62cb 100644
--- a/src/elisa/plot/scale.py
+++ b/src/elisa/plot/scale.py
@@ -140,7 +140,7 @@ def __init__(self, base: float, lin_thresh: float, lin_scale: float):
         self.base = base
         self.lin_thresh = lin_thresh
         self.lin_scale = lin_scale
-        self._lin_scale_adj = lin_scale / (1.0 - self.base**-1)
+        self._lin_scale_adj = lin_scale / (1.0 - 1.0 / self.base)
         self.inv_lin_thresh = lin_thresh * self._lin_scale_adj
 
     def transform_non_affine(self, values: np.ndarray):
@@ -163,7 +163,13 @@ def inverted(self):
 class _LinLogFormatter(LogFormatterSciNotation):
     """Formatter for LinLogScale axes ticks."""
 
-    def __init__(self, base: float, lin_thresh: float, lin_scale: float):
+    def __init__(
+        self,
+        base: float,
+        lin_thresh: float,
+        lin_scale: float,
+        label_only_base: bool = False,
+    ):
         base = float(base)
         lin_thresh = float(lin_thresh)
         lin_scale = float(lin_scale)
@@ -179,20 +185,35 @@ def __init__(self, base: float, lin_thresh: float, lin_scale: float):
         self.__lin_thresh = lin_thresh
         self.__lin_scale = lin_scale
         self._formatter_lin = ScalarFormatter()
-        super().__init__(base, linthresh=lin_thresh)
+        super().__init__(
+            base=base,
+            labelOnlyBase=label_only_base,
+            linthresh=lin_thresh,
+        )
 
     def __call__(self, x: float, pos: int | None = None):
         if x >= self.__lin_thresh:
             return super().__call__(x, pos)
         else:
-            return self._formatter_lin(x, pos)
+            s = self._formatter_lin(x, pos)
+            try:
+                if float(s) == 0.0:
+                    s = '0'
+            except ValueError:
+                pass
+            return s
 
     def set_axis(self, axis: Axis):
-        dummy = _DummyAxis(
-            axis, self.__base, self.__lin_thresh, self.__lin_scale, False
+        self._formatter_lin.set_axis(
+            _DummyAxis(
+                axis, self.__base, self.__lin_thresh, self.__lin_scale, False
+            )
+        )
+        super().set_axis(
+            _DummyAxis(
+                axis, self.__base, self.__lin_thresh, self.__lin_scale, True
+            )
         )
-        self._formatter_lin.set_axis(dummy)
-        super().set_axis(axis)
 
     def create_dummy_axis(self, **kwargs):
         self._formatter_lin.create_dummy_axis(**kwargs)
@@ -201,7 +222,8 @@ def create_dummy_axis(self, **kwargs):
     def set_locs(self, locs=None):
         """Set the locations of the ticks."""
         super().set_locs(locs)
-        self._formatter_lin.set_locs(locs)
+        lin_locs = [i for i in locs if i <= self.__lin_thresh]
+        self._formatter_lin.set_locs(lin_locs)
 
 
 class LinLogLocator(Locator):
@@ -294,21 +316,11 @@ def tick_values(self, vmin: float, vmax: float):
             ticks_log = self._locator_log()
             mask = np.greater(ticks_log, log_lower_lim)
             if mask.any():
-                ticks_log = ticks_log[mask]
-
-                # ignore the first major tick of log range if too close to 0
-                if not self._is_minor:
-                    t0 = ticks_log[0]
-                    fx = np.log(t0) / self._log_base
-                    if np.isclose(fx, round(fx)):
-                        t0_ = self.transform_non_affine(np.asarray([t0]))
-                        if t0_ < self._lin_scale_adj:
-                            ticks_log = ticks_log[1:]
-
-                ticks.append(ticks_log)
+                ticks.append(ticks_log[mask])
 
         if ticks:
             ticks = np.unique(np.hstack(ticks))
+
         return self.raise_if_exceeds(ticks)
 
     def view_limits(self, vmin, vmax):
@@ -397,10 +409,14 @@ def set_default_locators_and_formatters(self, axis):
             lin_thresh, lin_scale, base, 'auto', is_minor=True
         )
         axis.set_minor_locator(minor_locator)
-        minor_formatter = LogFormatterSciNotation(
-            base=self.base, labelOnlyBase=(self.subs is not None)
+        axis.set_minor_formatter(
+            _LinLogFormatter(
+                base,
+                lin_thresh,
+                lin_scale,
+                label_only_base=(self.subs is not None),
+            )
         )
-        axis.set_minor_formatter(minor_formatter)
 
     def get_transform(self):
         """Return the `.LinLogTransform` associated with this scale."""